3rd QUARTER 2020 ZAR25 | US$2.50 | Euro1.60
AI Expo Africa 2020 Show Issue
The Voice of African AI & Data Science Intel Sponsors AI in Youth Zone
SAP HEADLINES AI EXPO AFRICA 2020
Ethics in Ai
The Big Debate I’m sorry Dave, I’m afraid I can’t do that.
Microsoft’s AI Labs at AI Expo Africa
HUAWEI CLOUD JOINS AI EXPO LINE-UP
AFRICAN & GLOBAL AI LEADERS TO SPEAK AT AI EXPO AFRICA 2020
Dutch, Swiss, French & Israeli AI Companies Promote African Trade
Cape Town and the Western Cape Tech Capital of Africa We are a region of unlimited potential. And this translates into unlimited opportunity for those in tech. We have a world-class digital ecosystem, where resources and talent meet commercial and social opportunity. We are a region that sees digital disruption as less of a thing and more as a way of doing things. Our destination is a place with an interconnected business landscape, offering access to a shared economy, powered by tech-savvy investors. Our city is full of talented and highly skilled people, where opportunities to grow and make a global difference abound. We also have an unfair share of natural beauty. So itâ€™s no surprise that global tech companies choose our destination to have headquarters, as a springboard into growing markets, and as a place to work and play. Wesgro, the official tourism, trade and investment promotion agency for Cape Town and the Western Cape, can help you uncover these opportunities in the tech space.
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CONTENTS 3rd QUARTER 2020
4 SA’s President Ramaphosa Receives Report on 4IR 4 Egypt deploys AI-powered COVID-19 Diagnosis tool for the Deaf 6 AI Dialogue South Africa: Stakeholders commit to responsible AI Ecosystem 8 SA Fintech CompariSure raises VC Funding 8 Students from Kenya, Tunisia represent Africa at 2020 Imagine Cup EMEA Finals 10 Tackling Digital Inclusion: Just Makes Good (Business) Sense 12 SA’s Minister of Communication and Digital Technologies to open AI Expo Africa 2020 13 Young Enterprise Initiative South Africa 2020 Cohort to exhibit at AI Expo Africa 2020, Courtesy of French Embassy 14 Intel Sponsors ‘Youth in AI’ Pavilion at AI Expo Africa 14 Meet Vicki, AI Expo Africa 2020 ONLINE synthetic AI-powered Host 15 Sila Health among 30 Most Inspiring Digital Innovations of 2020 16 minoHealth, Imperial College London win £150k grant for molecular diagnostic project 18 Why Eliminating Bias in AI is Key to AI Success 20 Create a Safe & More Secure Workplace with Kenai 22 Higher Conversion through Artificia Intelligence 24 It’s 2020 26 Switzerland: a Safe Hub for AI 28 HUAWEI CLOUD – Building Inclusive AI 29 HUAWEI Intelligent Transport System Rolls out in Kenya 30 Pick n Pay implements ML earning to give Shoppers Personalised Discounts 31 Risk Insights Launches SA’s firs AI-developed ESG Sustainability Rating Tool 32 Tech Giant HUAWEI CLOUD joins AI Expo Africa 2020 as Headline Partner 33 UiPath software robots free employees to do higher value work. 34 Cracking machine learning to speed up client service 36 Tshimologong launches programme to help grow female-owned tech businesses 38 Ethical AI 42 UN Economic Commission of Africa partners with telcos on COVID-19 Communication Platform 43 HSRC, Facebook launch ethics and human rights in AI research initiative 44 Oracle: Getting innovation right in South Africa 46 FNB is leveraging AI to redefin risk management and ways of working 50 Naspers Foundry invests R100m in SA agritech startup Aerobotics 51 Report: The Global AI Agenda 52 Google for Startups Accelerator Africa 2020 53 Zindi and AI4D build language datasets for African NLP 56 1-Million Women in RPA by 2025 58 The PC is Back, and 2020 is it’s Year 60 Blue Prism’s Academia Program 62 Re-Skilling for the Future of Work that’s Happening Now 65 Israeli Companies leading the AI Industry 66 SA Academic elected Chair of UNESCO Ad Hoc Expert Group on Artificia Intelligence 67 Taking AI to New Frontiers 69 Leveraging Digital Technologies to Deliver Enhanced Data Insights with Microsoft 72 Guided by AI: How Renewable Africa 365 is applying AI in the rural electrificatio of Nigerian 76 Dotmodus: Using ML to Better the World 79 Cognizance Processing 80 Conversational AI Is Transforming Financial Services 82 Technology Matters, but Should it Follow or Lead? 86 Challenges of Thermal Cameras - HealthVision AI 92 Training the next generation for improved visual intelligence - Focus on Industry 4.0 94 The Future of Breast Imaging is NOW 98 Improving business decisions in an uncertain economy 100 Scaling Intelligence In Software Development 102 Covid-19 Project by Social Labs 104 WizzPass provides firs real-time COVID-19 screening solution both staff visitors 106 The 4IRI Mpumalanga Take Off 4IR Incubator - Scaling up to UpSkill How To Be The Disruptor Using AI 111 AI For Good - Time To Move The Needle by Fred Werner, Head, Strategic Engagement Division (TSB) at the International Telecommunication Union 112 How To Be The Disruptor Using AI by Neil Sahota, IBM Master Inventor, United Nations (UN) Artificia Intelligence (AI) Advisor
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Daniel Mpala Deputy Editor: News & Media
AS THE issue of ethics and morality take centre stage in the world of AI, Issue 9 of Synapse looks at the efforts being made by organisations like UNESCO and the EU to set policies that encourage and regulate the ethical use and development of AI technology. Closer to home, recently stakeholders in South Africa’s AI scene -- in a very encouraging move --committed to the ethical development and use of AI, agreeing that the technology should benefit everyone. The EOI signed at the AI Dialogue also covers several crucial areas which are set to positively impact the country’s AI ecosystem. With AI Expo 2020 just around the corner, you’ll want to read some of the insightful thought leadership articles on AI and Data Science from some of the speakers who’ll be giving talks at the show. Our pre-show edition of Synapse comes in August, which most will know is Women’s month in South Africa. Check out our Q&A feature with RPA Nuggets founder Tholang Mathopa who’s on a mission to train 1 million African women in RPA and Intelligent Automation. The future looks bright.
Watch the Latest AI TV Broadcasts
Nick Bradshaw AI Media CoFounder & Community Director 2020 IS the year of change for us all globally. COVID19 has impacted us all and gave birth to AI Expo Africa 2020 ONLINE as we moved our event online. Synapse is perhaps now serving even more the purpose and vision we originally intended to share the “good news story” of African AI & data science across the region. Two years on since launch we are proud to say our 9th edition is the biggest yet and one we hope you will enjoy. Join us online and let’s continue to celebrate the positives in these challenging times and marvel at the breadth and depth of the African 4IR journey.
Roy Bannister AI Media CoFounder & Editor-inChief WELCOME TO the Show Issue of Synapse Magazine. Ideally we would all be meeting face-to-face now at Africa’s largest AI event, but we’ve embarked upon an ambitious plan to host our event online, that will extend our reach across the continent. Welcome on this adventure with us. This issue has a strong focus on Ethics in AI, and our WorldClass speaker programme at the show reflects that, along with other pertinent AI debates, insights and knowledge. Our cover for this issue pays homage to 2001: A Space Odyssey and its autonomous AI, Hal 9000 - highlighting some of the complex issues around AI and Ethics.
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SA’S PRESIDENT Ramaphosa Receives Report on 4IR Urges placing 4th Industrial Revolution at the centre of South Africa’s economic recovery
PRESIDENT CYRIL Ramaphosa has urged the Presidential Commission on the Fourth Industrial Revolution (4IR) to place 4IR at the centre of South Africa’s economic recovery. “South Africa must be a more technologically driven country that finds solutions that move us forward, with 4IR as a pivot for economic recovery,” said President Ramaphosa. The President said digital transformation has to be harnessed “to change the way we live, learn, work and govern.” President Ramaphosa made the remarks in early August, when he received the recommendations contained in the report of the Presidential Commission on the Fourth Industrial Revolution (4IR). Communications and Digital Technologies Minister, Stella Ndabeni-Abrahams and Deputy Chairperson of the Commission, Professor Tshilidzi Marwala presented the report to the President. The Commission, which includes leaders from academia, business and civil society, began its work in May 2019, combining research and stakeholder engagements to generate a comprehensive view of South Africa’s current conditions as well as the prospects in the 4IR. The Commission has since its establishment deliberated on the opportunities that enable South Africa to craft a shared 4IR
future, as well as the constraints that are currently in place. These deliberations have included international benchmarking which has delivered insights into the possibilities for the competitive positioning of South Africa in the 4IR landscape globally. The Commission has also examined the role of the state, as well as key institutional actors, in leading and resourcing the work that must be undertaken to ensure success. The Commission has made recommendations spanning such strategic areas as the country’s investment in human capital; artificial intelligence; advanced manufacturing and new materials; the provision of data to enable innovation; future industries and 4IR infrastructure. President Ramaphosa welcomed the report, which the Commission will shortly present to Cabinet before the report is published. It is not clear when the report will be published. Following its publication, the report will form the basis of a national discussion on how all sectors of society can contribute to a technologically enabled future that brings about greater economic and social inclusion, and enhances the competitiveness of the South African economy. This article was originally published by SAnews.gov.za here ai
EGYPT DEPLOYS AI-POWERED COVID-19 diagnosis tool for the deaf, hard of hearing Egypt’s Ministry of Communications and Information Technology (MCIT) in June joined forces with the United Nations Development Programme (UNDP) and Avaya Holdings Corp to launch a chatbot that uses artificial intelligence (AI) to enable sign-language based interaction and the provision of intuitive access to critical COVID-19 related information and support.
THE CHATBOT, which Avaya said was a world first, will extend the capabilities of WASEL — MCIT’s dedicated contact service centre service for people living with disabilities. The service is available via the Tamkeen website or WASEL smartphone app. The initiative aligns with MCIT’s efforts to support the Egyptian government’s plan to effectively mitigate COVID-19 challenges, and the state’s vision of deepening social integration by utilising smart technologies that foster inclusivity through all segments of society. ai
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AI DIALOGUE SOUTH AFRICA:
Stakeholders commit to responsible AI Ecosystem
3RD QUARTER 2020
AI Dialogue South Africa, a virtual event which was held in early August, saw stakeholders in South Africa’s AI industry commit — through an expression of interest (EOI) — to building AI technologies that are not only beneficial to everyone but also adhere to the country’s constitution and bill of rights.
THE EVENT, which was organised by Convergence Partners, Accenture, University of Johannesburg, Digital Council Africa and Sun & Shield Technologies, sought to find common ground in using AI as a driver for economic growth, social development and safety. The virtual event was attended by members of South Africa’s tech industry, startups, SMMEs, academics, AI researchers, policy makers as well as government officials. Other areas touched on by the EOI — a draft of which can be viewed here includes: • Private sector establishment of a South Africa AI fund and AI Institute • Grants for research by academia • Funding for AI start-ups, incubators and accelerators • Development of an AI School curriculum for early introduction
in school • Support for the export of local AI initiatives, products, services and solutions • Establishment of an AI market place for AI startups • An annual AI symposium for all stakeholders • Establishment of private sector work-streams across the health, education, mining and automotive • Negotiation of a five-year tax holiday for AI companies • Representation of South Africa in Global AI forum and initiatives • Representation in global AI competitions • Engagement in bilateral knowledge transfers with other AI global institutes • Awareness master class seminars for labour, and society at large ai
STUDENT TEAMS FROM KENYA, Tunisia represent Africa at 2020 Imagine Cup EMEA finals Two student teams from Kenya and Tunisia represented Africa at the 2020 Imagine Cup finals on 19 and 20 May after beating three other teams from Kenya, Ukraine and the UK at the EMEA regional finals in March.
THE IMAGINE Cup, a Microsoft global technology competition, aims to inspire students to use their imagination and passion for technology to create innovative and inclusive projects that tackle some of the world’s biggest social, environmental, and health challenges. The Kenyan team, The Knights, comprised two Jomo Kenyatta University of Agriculture and Technology students Michael Malombo Mwaisakenyi and Ken Kioria Gicira. The duo created an automated robot which uses artificial intelligence (AI) to identify and remove weeds from rows of crops. Their solution uses cameras as sensors to gather input from The Knights team, Kenya the environment and eliminate farmers’ need to use environmentally harmful pesticides in their weeding. The robot can be used by anybody and does not require technical skills to operate. The team made sure that the farmer needs only to place the robot at a given part of the farm, and it will do the rest. Microsoft Azure technology that the team uses includes App Services for mobile and web, Storage, analytics, and Cognitive Services.
Red Walls team, Tunisia The Tunisian team, Red Walls, comprised three National Institute Applied Science and Technology students, namely Mohamed Said Fayache, Achraf Feydi, Meriem Zhang. The trio created I-Remember, a two-part mobile application designed for the well-being of both Alzheimer’s patients and their caregivers. The patient interface includes task reminders, live facial recognition, labelled photos, emergency location and call assistance, as well as memory games to help evaluate and train the user’s memory. The caregiver interface provides the same, but with supervisor features. The team uses Microsoft Azure Storage, containers, and Cognitive Services. Both teams each won $8 000, Azure credits and a spot to compete at the finals which were won by a team fromHong Kong. Check out The Knights pitch here and Red Walls pitch here. Register for the Imagine Cup 2021.
3RD QUARTER 2020
SA FINTECH COMPARISURE
raises Venture Capital Funding from Umkathi Wethu Ventures
Cape Town based fintech startup CompariSure announced in May that it had raised an undisclosed amount of venture capital funding from Umkathi Wethu Ventures in partnership with Allan Gray.
8 CompariSure founder Jonathan Elcock (left) with cofounder Matthew Kloos (right)
COMPARISURE, WHICH was founded in 2017 by Jonathan Elcock, distributes financial services via its proprietary chatbot technology which leverages the Facebook Messenger and Whatsapp platforms. The startup is an accredited distributor of cover for Sanlam, Old Mutual and Momentum. CompariSure’s deal with Umkathi Wethu Ventures is the startup’s second venture capital investment, with 4Di Capital having invested an undisclosed amount in the firm last August. ai
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TACKLING DIGITAL INCLUSION: Just Makes Good (Business) Sense Forget clogs, tulips and weed, the Dutch bring a lot more to the international business table. Think instead #sustainability #innovation #cocreation - critical blocks to any successful business collaboration. By Sebastiaan Messerschmidt,Consul General of the Kingdom of the Netherlands & Nichi Walker-Woodard, Deputy Consul General AND THIS is no different in the Artificial Intelligence arena. AI is no doubt set to become the defining technology of the future and the Netherlands has carefully built its foundations for a solid AI policy and strategy. Developing a competitive economy to maximise the benefits that AI technologies can bring to the Netherlands and the nations it trades with, the country’s main idea is to fund applied technical research supported by social research.
“ 3RD QUARTER 2020
Forget clogs, tulips and weed, the Dutch bring a lot more to the international business table. Think instead #sustainability #innovation #cocreation - critical blocks to any successful business collaboration.
Sebastiaan Messerschmidt, Consul General of the Kingdom of the Netherlands
This is achieved through the Dutch Triple Helix approach (Government, Private Sector and Knowledge Institutes working together) which has contributed significantly to the Netherlands having one of the strongest economies in the world. Innovative, sustainable solutions arising from these critical collaborations are then taken to market where relationships are built and the demand side is kept at the core of all engagements. But understanding local demand in the African context is no mean feat, and requires ongoing investment into understanding the complexities of the local ecosystem. The annual #cocreateDESIGN Festival, an initiative of the Kingdom of the Netherlands in South Africa, is one such example. It engages people with Nichi Walker-Woodard, local and Dutch business communities Deputy Consul General
and civil society organisations, all to tackle current socio-economic and environmental challenges through the power of design thinking. This year’s festival hosted in Langa, Cape Town tackled the complexities of the Fourth Industrial Revolution in the African context with the theme ‘Towards Digital Inclusion’. Understanding 4IR as the convergence of our physical environment, cybernetics and the biomedical worlds, the consensus amongst festival participants was that the fourth industrial revolution is very much with us in South Africa and is fundamentally impacting on the way people live, work and interact with each other. Participants also agreed though that this is not the reality for everyone, as the numbers of disadvantaged are growing (e.g. over 30% unemployment rate) and access to (very expensive) digital technology is not for the masses. Indeed South Africa, often experiencing debilitating daily load-shedding, could be said to be stuck in the 2nd and 3rd industrial revolutions too. This is not an easy context for doing business, but the most successful businesses entering the market will be those who recognise this, as they #cocreate, #innovate and build sustainable solutions (whilst making a good return on investment of course). And so this year’s AI Expo Africa brings an exciting opportunity to the Dutch business community operating in this space. From agriculture to water, transport and logistics to health sciences, energy solutions to creative industries, we are looking forward to #cocreating and #innovating- make sure you join us at our business table and get the conversation going. ai
SA’S MINISTER OF
Communication and Digital Technologies to open AI Expo Africa 2020 South Africa’s Minister of Communications and Digital Technologies Stella Ndabeni-Abrahams is set to deliver the opening keynote at AI Expo Africa 2020.
Tshilidzi Marwala, and Vice-Chancellor of the University of Johannesburg and Deputy Head of the 4IR Commission of South Africa. AI Expo Africa 2020 has drawn heavyweight vendors like SAP, Huawei Cloud, Blue Prism, UiPath, Intel, Dell, Microsoft and Genesys who will be exhibiting their solutions and products at the expo. They will be joined by a contingent of local startups that includes Ashanti AI, Botlhale AI Solutions, DotModus, Predictive Insights, FinChatBot, FIRtech, Learning Machines, Kenai, Heat Vision A.I, WizzPass, Zindi, Synthesis and Future Fragment. The expo will also feature dedicated French, Dutch and Swiss pavilions where startups from the three respective countries will showcase their AI and Data Science innovations and solutions. In addition, delegates can also look forward to an Intel Youth in AI ePavilion which aims to foster inclusion of youthfocused AI entities and initiatives. ai
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MINISTER NDABENI-ABRAHAMS stated, “This event is taking place at a time when the whole world is grappling with new realities and a new normal brought about by the advent of the COVID-19 pandemic. Advances in artificial intelligence technologies hold the promise of bringing us closer to finding lasting solutions to help us solve the challenges we are facing as humanity. The world is undergoing fundamental changes due to advances in technology and progress made in the field of artificial intelligence (AI). Similarly the continent and my country South Africa, are going through same profound changes” This year’s speaker line-up features keynotes by Kay Firth-Butterfield, Head of AI and Machine Learning at the World Economic Forum; Neil Sahota, IBM Master Inventor, UN AI expert and lecturer at University of California, and Fred Werner, Head of Strategic Engagement at the International Telecommunication Union, and Bayo Adekanmbi, CTO MTN Nigeria and founder of Data Science Nigeria, as well as Prof
Telecommunications Minister Stella Ndabeni-Abrahams (centre) visits AI Expo Africa
YOUNG ENTERPRISE INITIATIVE
South Africa 2020 Cohort to exhibit at AI Expo Africa 2020, Courtesy of French Embassy
meetings that Bécue says are designed MATHIEU BÉCUE, Attaché for Innovation at to allow each laureate to benefit from an the French Embassy, explains that the Yei extensive customized business network Start in France programme – which YEi South and connections to the best resources in Africa falls under – was founded in 2005 as Europe. The trip has now been postponed to an accelerator for science startups looking to October because of the COVID-19 pandemic. develop and grow their businesses in France 3DIMO co-founder Nneile Nkholise says the and Europe. YEi South Africa programme has helped her The French Embassy then launched Yei realise the potential her company has to create South Africa in 2016 in partnership with the relationships in the French market. Nkholise Technology Innovation Agency (TIA) with the points out that France has been investing intention to provide South African startups heavily in creating a thriving AI community with the opportunity to develop and grow and creating opportunities for non-French their businesses in France. South Africa is tech companies to establish businesses in the currently the only country on the African country. continent to benefit from this programme. “Although there have been delays in us The French Embassy together with TIA Raphta founder Tshidiso fully experiencing the opportunities of YEi have now sponsored 3DIMO, Raphta and Radinne programme due to Covid-19 pandemic, I’m Ubiquity to participate at AI Expo Africa 2020 – thankful that I have been given an opportunity Africa’s largest AI, Robotic Process Automation to be part of the AI community in South Africa and France. (RPA) and data science trade-focused show and conference That will benefit the sustainable growth of our company and – which will this year be held as a virtual event on 3 and 4 help transform society using emerging opportunities from AI September. technology,” she adds. 3DIMO has developed an automated livestock data Raphta founder Tshidiso Radinne says the YEi South Africa analytics and modelling platform. Raphta offers world-class programme has catapulted his firm into a “global AI startup”, and pioneering computer vision, facial recognition and imaging assisted the company in executing its Europe, Middle East and technology. Ubiquity AI has over six years commercial Africa expansion plan by establishing a presence in France – a experience in Natural Language Processing (NLP) as the first data-at-rest social analytics consultancy in Africa and the Middle key European market. “We have a core focus on fundamental and applied research East. The startup has developed Simone, a chatbot which it in cutting edge areas such as the combination of quantum claims to be the world’s first debt intermediator. imaging and machine learning, and our research partnerships The Yei 2020 cohort were initially meant to travel with leading French universities through the YEI are vital to our to France for a two week-long immersion trip which research ecosystems,” adds Radinne. ai includes training sessions, networking and one-on-one
3RD QUARTER 2020
The French Embassy in South Africa has announced that the three South African artificial intelligence (AI) startups that were selected last year to participate in its Young Enterprise Initiative South Africa (YEi South Africa) 2020 programme – 3DIMO, Raphta, and Ubiquity AI – will exhibit their solutions and products at AI Expo Africa 2020.
INTEL ‘YOUTH IN AI EPAVILION’
at AI Expo Africa 2020 to Promote Inclusion of Youth-Focused Initiatives, Organisations Intel is set to promote inclusion of African youth in Artificial Intelligence (AI) through the ‘Intel Youth in AI ePavilion’ at AI Expo Africa 2020, this after the industry-leading tech firm signed up to sponsor nine youth-focused companies and organisations to exhibit at this year’s expo.
THE INTEL ‘Youth in AI ePavilion’ will promote and showcase youth-focused AI companies and organisations, as well as Science, Technology, Engineering and Mathematics (STEM) initiatives. Roy Bannister, co-founder of AI Media Group and director of AI Expo Africa show production stated: “We’re delighted to welcome Intel back as a sponsor this year, especially given their focus on skills development and great support in the past, where Intel assisted us in providing free AI Workshops to a large number of data science students, young engineers and entrepreneurs.” Nick Bradshaw, co-founder of AI Media Group — curators of AI Expo Africa stated, “With the impact of COVID, we have taken the entire community online this year. It means we can reach more countries and include
more people. Uniquely this platform not only allows us to run our two-day business event, but it also serves as a 30-day learning platform after the main event ends. All the talks, vendor booths, posters and content are available for young people, students, entrepreneurs and learners from across South Africa and wider Africa to join us and learn about the latest technology driving the Fourth Industrial Revolution in Africa”. “We thank Intel for supporting this aspect of our show as this is a great opportunity for young people to learn about the Fourth Industrial Revolution and even find a job. The reach of this online eConference and Youth AI component will be bigger than our previous two shows — we can’t wait to welcome everyone on the 3rd of September,” concluded Bradshaw. ai
Meet Vicki, AI Expo Africa 2020 ONLINE synthetic AI-powered Host
3RD QUARTER 2020
Delegates to AI Expo Africa 2020 ONLINE will be welcomed at the virtual show by Vicki, a synthetic AI-powered host which will also be seen introducing keynote speakers.
AI EXPO Africa organisers AI Media Group were like other companies pushed into new ways of working by the COVID-19 pandemic, more so as large gatherings and face-to-face conferences are no longer possible. Coming off the back of highly successful shows in 2018 and 2019, the AI Expo Africa team has had to come up with a new way to host the event and continue to add value to the show’s delegates, speakers, and sponsors. Roy Bannister, COO AI Media Group and AI Expo Africa cofounder, says the team decided to replicate the format used for the previous shows online and make a “digital twin” of the event. “We spent 2 months looking at options and decided to choose a dedicated eConference platform that allows us to mix live and re-corded elements that will make for a great experience for the community,” added Bannister. The two-day Live Online Programme has a mix of live interaction spaces such as the virtual vendor hall with eBooths, as well as dedicated speaker and networking lounges where
delegates can hold live interactive meetings on video or via chat. In addition, delegates will be able to hold Q&As with speakers via a secure, invite only eConference platform. Nick Bradshaw, CEO AI Media Group and AI Expo Africa co-founder, says Vicki is perhaps the “greatest innovation” at this year’s show. “Vicki is the first 100% synthetic AI powered host of AI Expo Africa 2020. She is working at the show to introduce the main keynote speakers during the opening sessions of Day 1 and Day 2 of the show. This technology has come a long way and will be showcased at the event. It’s becoming harder to tell the difference between real humans and synthetic actors, which is both an amazing innovation but also provokes interesting reactions, especially in the era of fake news and deep fakes. She is a testimony to how far this technology has come and we can assure our audience everything she says is true!” added Bradshaw. ai
SILA HEALTH AMONG
30 Most Inspiring Digital
Innovations of 2020
Sila Health, a health tech startup that provides last-mile healthcare access across Africa using chat platforms and machine learning, has been named among the 30 Most Inspiring Digital Innovations of 2020.
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THE AMSTERDAM-BASED startup — which was cofounded in 2019 by Zimbabwean Babusi Nyoni together with Gijs Corstens — received the award alongside Oxfam India and Plan International in recognition of its work in using machine learning to bridge the health gap across Africa. The awards were organised by The Spindle, the innovation programme of Partos, the Dutch Association for NGOs working in international development. Sila Health was selected from among 60 applicants by an expert group which consists of digital experts from Kenya, Bangladesh. Other African Artificial Intelligence (AI) and Data Science initiatives which were selected for the awards include Ghanaian data science institute Blossom Academy and Rwanda’s Care Me E-Clinic which is developing an AI-powered intelligence platform where a patient can record their data to build a comprehensive medical history. Check out Synapse’s feature on Sila Health here and learn about the other African initiatives that made it into the 30 Most Inspiring Digital Innovations of 2020 here. ai
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Minohealth, Imperial College London win £150k grant for molecular diagnostic project
The Ghana News Agency reported in late July that Ghanaian data science startup minoHealth AI Labs in partnership with Imperial College London won a grant of up to £150 000 from the UK Research and Innovation (UKRI) Digital Innovation for Development in Africa (DIDA) to test, improve and deploy a handheld digital molecular diagnostic device and platform called Lacewing.
INITIATED BY Imperial College London, Lacewing is a lab-on-a-chip device that allows for rapid diagnosis of infectious diseases like malaria, with results comparable to Polymerase Chain Reaction (PCR). It is reported that Lacewing has already been adapted to COVID-19, with reports that it can identify the virus that causes COVID-19 in under 30 minutes. minoHealth AI Labs will serve as Imperial College London’s AI partner on the project, working on AI and data science systems that will be used within the platform. minoHealth AI Labs founder Darlington Akogo told Ghana
News Agency that the project aims to test, improve and deploy the system “especially in Africa” in the fight against Malaria and other infectious diseases. Akogo, who will also be speaking at AI Expo Africa 2020, added that the Lacewing system will collect geographic information for each diagnostic which the project will use to map infectious diseases and their spread. “We’d then be developing machine learning-based forecasting models to predict the further spread of malaria, as well as other infectious diseases we adapt to it. ai
Ford South Africa Launches AI-powered Self-Service Tool ‘Ask Ford’
3RD QUARTER 2020
Ford Motor Company of Southern Africa (FMCSA) in June launched Ask Ford, an intuitive global online knowledge base tool for customers.
LOCATED ON the www.ford.co.za website and accessed via the magnifying glass icon, the self-service tool is available 24 hours a day, seven days a week. Ask Ford enables customers to ask questions anytime and receive immediate answers that are retrieved directly from Ford systems, owner’s manuals or Ford websites. FMCSA explained that Ask Ford uses the repository’s artificial intelligence (AI) technology to search for the best responses, far beyond the reaches of standard search engines. The self-service tool uses artificial narrow intelligence (ANI) and patented natural language processing capabilities. It is designed to produce accurate, relevant answers to a wide variety of questions, which FMCSA said will deliver enhanced user experience for consumers. FMCSA explained that the intelligent system learns through each use about related topics, and how to provide relevant answers. Ford said this will enable it to continually improve the user experience, meaning the more it is used, the better it will get. A survey is incorporated into the Ask Ford page, giving users the opportunity to select a star rating and provide feedback so the system can be improved. Besides its benefits to current or prospective Ford customers, Ask Ford also has specific channels designed
to support Ford dealers and FMCSA’s national Customer Relationship Centre (CRC) staff, thereby assisting them in obtaining the most up-to-date and precise information related to specific customer queries. “Ask Ford is a proven global knowledge base tool for customers, dealers and Ford staff, and is already used in over 25 Ford markets globally serving several languages,” said Neale Hill, managing director of FMCSA. “We are excited to be introducing Ask Ford to the South African market, as it significantly enhances our ability to instantly provide accurate and detailed information for our customers,” added Hill. ai
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WHY ELIMINATING BIAS IN AI is Key to AI Success
2020 is forcing us to confront some hard truths about the world we live in. The Covid-19 pandemic has cast a sobering spotlight on some of the more questionable facets of our way of life and is making it clear, that continuing on this unsustainable path we have been on will inevitably lead to a very bleak future for our species. By Rudeon Snell, Global Senior Director: Industries & Customer Advisory at SAP
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ONE SUCH truth is symbolised by the global #BlackLivesMatter movement, which was sparked in the US, but has spread to cities all around the globe. This movement has once again highlighted the embedded biases in our interconnected social fabric, forcing us all, to not only rethink, but completely reevaluate long standing notions of morality, fairness and ethics. It is worth taking pause, just for a moment, to consider whether the exponential technological progress we have been experiencing, and which does aim to create a better future for humanity, is not also amplifying some of the very same challenges we are trying to overcome as a global society.
As we strive to meet the unmet and unarticulated needs of customers, we continuously look towards technology to fulfil the promise of ushering in a new era of human advancement. We see leading companies globally investing heavily in technologies such as Cloud Computing, Internet of Things, Advanced Analytics, Edge Computing, Virtual and Augmented reality, 3-D printing and of course Artificial Intelligence. And it is AI, which many experts tout as one of the most transformational technologies of our time, perhaps even more transformational than electricity or fire, in terms of sheer impact on humanity. Global use of AI has ballooned by 270% over the past five years, with estimated revenues of more than $118-billion by 2025. AI powered technology solutions have become so pervasive, a recent Gallup poll found that nearly 9 in 10 Americans use AI based solutions in their everyday lives. Phones, apps, search engines, social media, email, cars and even appliances in our homes are all powered by AI infused technologies today, with this trend set to accelerate in future. And yet, a dark side of AI is surfacing with alarming frequency as AI engrains itself in our daily lives. Questions that
are increasingly being posed and must be addressed, concern themselves with whether AI algorithms are indeed perpetuating various forms of bias to the detriment of under-represented communities and minorities? To what extent do AI-imbued solutions discriminate against exposed classes of our society due to embedded bias?
Bias in the machine
There are ample examples of algorithms displaying forms of bias. In 2018, reports emerged of Gmail’s predictive text tool automatically assigning “investor” as “male”. When a research scientist typed “I am meeting an investor next week”, Gmail’s Smart Compose tool thought they would want to follow up with the question “Do you want to meet him?”. That same year, Amazon had to decommission their AIpowered talent acquisition system after it appeared to favour male candidates. The software seemingly downgraded female candidates if their resumes included phrases with the word “women’s” in them, for example “women’s hockey club captain”. Many of the large tech firms battle with diversity, with men much better represented than women in most major tech companies. Having gender bias embedded in algorithms designed to support the hiring process presents a significant risk to efforts at achieving greater diversity: Mercer’s Global Talent Trends report for 2019 highlights that 88% of companies globally, already use AI powered solutions in some way for HR, with 100% of Chinese firms and 83% of US employers relying on some form of AI for HR. For Amazon, it has forced a rethink of how they recruit globally, no small feat for a company that employs more than 575 000 workers.
Persecuted by an algorithm
Errant algorithms can be responsible for greater harm than just a few missed employment opportunities. In June 2020, the New York Times reported on an African American man wrongfully arrested for a crime he didn’t commit after a flawed match from a facial recognition algorithm. Experts at the time believed it was the first such case to be tested in US courts. I’d wager, it won’t be the last. Recent studies by MIT found that facial recognition software, used by US police departments for decades, works relatively well on certain demographics, but is far less effective on other demographics, mainly due to a lack of diversity in the data that the developers used to train these algorithms.
How bias enters our algorithms
McKinsey supports the view, that it is actually the underlying data that is the culprit in perpetuating bias, more so than the actual algorithm itself. In a 2019 paper, the firm argued that algorithms trained on data containing human decisions have a natural tendency toward bias. For example, using news articles for natural language processing could instil the common gender stereotypes we find in society simply due to the nature of the language used. Many of the early algorithms were also trained using web data, which is often rife with our raw, unfiltered thoughts and prejudices. A person commenting anonymously on an online forum arguably has more freedom to display prejudices without much consequence. It’s not socially acceptable to admit to being racist or sexist, but anonymity offered by the web means many of these views proliferate mainstream and niche websites. Any algorithm trained on this data is likely to assimilate the embedded biases. As Princeton researcher Olga Russakovsky observes: “Debiasing humans is a lot harder than debiasing AI systems.” One example of this is Microsoft’s well-intentioned experiment with their chatbot, Tay. Tay was plugged directly into Twitter, where users across the world could interact with it. Users of the popular social media platform promptly got to work teaching the bot racist, misogynistic phrases. Within one day, the bot started praising Hitler, forcing Microsoft researchers to pull the experiment. The lesson: algorithms learn precisely what you teach them, consciously or unconsciously. And because algorithms learn from data, data matters. Web data is also not fairly representative of society at large: issues with access to connectivity and the cost of smartphones and data could exclude many - especially minorities - from engaging with online content. This means that data collected from the web is naturally skewed to the demographics that make most use of websites and social media.
Combating bias in our AI solutions
One of the biggest challenges for the creators of AI algorithms trying to eliminate bias, besides merely identifying it, is knowing what should replace it. If fairness is the opposite of bias, how do you define fairness? Princeton computer scientist Arvind Narayanan argues
there are at least 21 different definitions of fairness, ranging across notions of individual fairness, group fairness, process fairness, diversity and representation. Our individual and collective life experiences will largely determine what type of fairness we favour, but the problem this creates is that one person’s fairness could be another’s discrimination. For example, what is the fair demographic representation of “Global CEO” when you enter that into an image search bar? Is it a 50/50 split between male and female? Is it an equal split between White, Black, Hispanic and Asian CEOs? Or should its results simply be proportional to real-world data: if there are only four black CEOs of Fortune 500 companies, should only 0.8% of search results be of black CEOs? There is arguably a need for greater diversity in the development rooms where AI algorithms are created. A cursory glance at the demographics of the big tech firms shows a disproportionate gender and demographic bias. More must be done to accelerate the synthesis of diverse and inclusive perspectives in the AI creation process, so that AI algorithms and the data they are trained on embody a broad range of perspectives, allowing them to drive more optimal outcomes for all those represented in society. What can we do to mitigate bias in the AI solutions we increasingly use to make potentially life changing decisions, such as arresting someone or hiring someone? Greater awareness of bias can help developers see the context in which AI could amplify embedded bias and guide them to put corrective measures in place. Testing processes should also be developed with bias in mind: AI creators should deliberately create processes and practices that test for and correct bias. Design should always keep bias in mind. It’s probably impossible to have a completely unbiased society, but having more diverse voices and greater awareness of the various forms of embedded bias within our societies can help AI creators build greater fairness into their algorithms. Diversity is important and can lead to more meaningful and helpful discussions around potential bias in human decisions. Finally, AI firms need to make investments into bias research, partnering with other disciplines far beyond technology such as psychology or philosophy, and share the learnings broadly to ensure all the algorithms we use can operate alongside humans in a responsible and helpful manner. Fixing bias is not something we can do overnight. It’s a process, just like solving discrimination in any other part of society. However, with greater awareness and a purposeful approach to combating bias, AI algorithm creators have a hugely influential role to play in helping establish a more fair and just society for everyone. This could be one silver lining in the ominous cloud that is 2020. ai
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Microsoft and Amazon have halted sales of their facial recognition software until there is a better understanding and mitigation of their impact, on especially vulnerable or minority communities. IBM has even gone as far to halt offering, developing or researching facial recognition technology. But how does this happen in the first place?
If fairness is the opposite of bias, how do you define fairness? - Rudeon Snell, Global Senior Director: Industries & Customer Advisory at SAP
CREATE A SAFE & MORE
Secure Workplace with Kenai One of the biggest impacts of COVID-19 has been on the workplace. The first wave of adjusting to work from home has been replaced with uncertainty about how companies will safely manage the return of their employees to the office. This, along with non-employee attendees like visitors, contractors and others, has created a challenge for health and safety teams worldwide as they struggle to create a safe environment for their stakeholders.
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AT KENAI, weâ€™ve been hard at work to solve this problem for our clients. Already managing the visitors and vehicles for many leading companies in sub-Saharan Africa (Deloitte, Total, Massmart, TransUnion to name a few) we actively sought to understand the key pain points experienced across different workplaces in managing the return to work. The major challenges identified have been employee and visitor screening before they come to work, touchless sign in, automatic notifications based on certain responses, logged temperature checking and integration into existing systems. Weâ€™ve adapted the trusted Kenai solution to cater for these points. Visitors and employees pre-screen themselves before coming to site and are automatically notified (as are the companyâ€™s health and safety officers) if they raised a red flag with their responses. On-site, they perform a touchless sign in using QR codes or facial recognition at the Kenai kiosk, confirm compliance with various safety protocols and have their temperature logged to their profile if required. Clear
communication throughout the process, the touchless nature and live data capture have resulted in our clients successfully managing the return of staff and visitors to their office without issue. Kenai brings together a number of cutting-edge technologies to make this happen. Firstly, facial recognition and QR codes make the process fast, secure and touchless. Live data capture and safety notifications create real-time insights. Flexible and functional design make the solution adaptable to meet the needs of diverse companies. Finally, integration into existing systems ensures a smooth change management process. The result is a smart, efficient and secure system that creates the environment companies need to confidently reopen their offices. Kenai will be exhibiting at AI Expo Africa 2020, visit their booth for more information on their solution. ai
through Artiﬁcial ntelligence
Digital marketing operations are not realising their desired financial benefits from converting captured leads into sales. An important factor is the inability to contact and influence the buying interests of prospects, according to Pieter van Eyssen, Principal Solution Consultant at Genesys South East Africa. Fortunately, the conversation rate and by extension, lead conversion and sales, can be significantly increased by using the correct software. Van Eyssen: ‘Data, communication and people, supported by artificial intelligence (AI), play a crucial role in this.’ By Pieter van Eyssen, Principal Solution Consultant at Genesys South East Africa
Digital marketing on the rise
Worldwide, more than 200 billion US dollars is spent on forms of digital advertising annually and this spend is projected to increase significantly as businesses around the globe adjust to new ways of reaching their customers and prospects. However, according to Pieter van Eyssen, digital marketing is delivering a low return on investment. The average conversion rate ranges between 2 and 4 percent. A primary reason is that organisations often do not respond to potential buyers within the short window of time in which real-time engagement and journey shaping has the most positive impact. “Leveraging AI to predict the right time, right communication channel and right prospect to engage, enable organisations to act faster and get in touch with an online lead before interest is lost. This greatly increases the chance that prospects will purchase from you. Research shows that the moment you get in touch is important. If you wait half a day, an hour or 2, or even down to a few minutes, the momentum has gone. An online prospect is easily lost. That is why Moments Connected is the slogan of Genesys.”
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Contact at the right moment
Finding the right moment of contact can be done with Predictive Engagement from Genesys. This is based on AI with a guiding, human hand. By means of indicative probability enabled by sequence learning and journey tracking the software provides insight in the opportunity or capability to engage the prospect. It looks for the moment when the probability of a successful sale or outcome decreases significantly or when the prospect’s journey indicates interest in a product or item. If a successful conversion is increasing, do nothing. If the probability decreases significantly from a prior high probability, the chance of conversion is greatest, Van Eyssen explains. “As an example, a prospect has just clicked on a banner and their clicking behaviour and journey shows that they have the intention to buy, but they do not actually click on the purchase button. With our software we can predict the right moment for intervention in order to prevent the prospect from disengaging. Digital marketing operations can automatically launch a chatbot that offers the prospect assistance. The software can also be put into action earlier. For example, someone is looking for a flight ticket to
Indonesia, Predictive Engagement can execute a popup with an appropriate offer.” According to Van Eyssen, the number of prospects or leads lost can be reduced by 30 percent and several businesses using Predictive Engagement have improved their conversion rate by a factor of 14.
Matching prospect and employee
Equally important is selecting the right employee to interact with the prospect, says Van Eyssen. Also using AI, Predictive Routing can select the right employee to connect to the prospect at the moment of truth. “Predictive Routing is used to intelligently schedule and roster employees that are most capable of facilitating a positive interaction with a prospect. A large amount of data on these employees is already available within the business. If an organisation, for example, wants to contact someone based on a certain campaign, we can ensure that the prospect and employee are matched at the right moment. In other words, the software can decide to postpone keep a prospect on hold for a short while, because an employee who is more suited to handling the interaction with the prospect, will be available in twenty seconds. This substantially increases the chance of a success. Besides increasing conversion, this also helps to achieve the highest possible customer loyalty, thus maximising the return on investment of a digital marketing campaign.”
The crux is the sharing of data. Data is collected across all business areas but most often it is siloed and not consolidated for optimal benefit. “We can achieve a substantial increase in return of investment for the marketing department by enabling collaboration with the sales and service areas and overcoming siloed operations”, says van Eyssen. “In partnership with our clients, Genesys establishes the most appropriate solution for their specific requirements. This process may include engagement with the contact centre, operations, services, sales, marketing and IT stakeholders, focusing on operational and strategic requirements as well as the desired business outcomes from both a process and technology perspective.’ Genesys will be exhibiting at AI Expo Africa 2020, check out their booth for more information about their products and services. ai
Sell Faster and More to your Digital Customer The industry average conversion rate from qualified leads to sales is around 2%. This conversion rate is so low because businesses are drowning in data and are unable to utilise the human touch in a smart way. Engagements are too late and disconnected from the journey. Sales teams canâ€™t have meaningful interactions as the right data is too hard to find. In this demo you will learn how Artificial Intelligence can help by predicting outcomes and triggering engagements with the right sales resource in real time, at the right time, with the right prospect. Get inspired by Genesys to learn more! www.genesys.com
IT’S 2020 With the world in the firm grip of the COVID-19 pandemic, it is a year that many people would soon want to forget. Although it is unclear when this pandemic would come to an end, it is sure to have a lasting impact on our economy, society and the very nature of how we live, work and communicate with each other. By Fred Senekal, Head of Research and Development, Learning Machines BUT THE world is also changing in a more fundamental way. It is a world in which technology is shaping the future. A world where the boundaries between the physical, digital and biological worlds are starting to blur. A world where artificial intelligence, robotics, genetic engineering and quantum computing will become part of our daily lives. Now, more than ever before, it seems that the complete automation of production, distribution and service are within humanity’s reach. It is a future where we will see many tasks currently undertaken by humans being executed by algorithms and robots at much greater speed and efficiency than what is currently possible. Is this future competitive? You bet it is. Only those organisations which are adapting with great speed to the current technological revolution will survive. Which begs the question:
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Are you ready for this future?
Perhaps it is time to take stock of what an organisation is per se. An organisation is not just a set of people, tasks, processes, products or buildings. In many ways, it exhibits the properties of a living organism that needs to optimise its structure and behaviour in order to compete favourably in the market and ultimately survive. Just as machine learning could be applied to optimise individual tasks and processes in an organisation, the principles underlying machine learning can be applied to organisations as a whole. The study of artificial intelligence is often known as the study of intelligent agents . The concept of intelligent agent can be applied to living organisms, machine learning algorithms, robots operating in a human environment, organisations, or even entire economies. Such an intelligent agent always operates in an environment. The environment of a software algorithm is fairly simple - it has a clearly defined set of inputs and outputs that completely describe how it interacts with its environment (the software and hardware that it is part of). On the other hand, the environment of an organisation is far more complex - it has many different people and business units interacting with customers, stakeholders and other entities, various social, economic, political and environmental considerations and it has to compete with other intelligent agents operating in the same environment. If we now view an organisation as such an intelligent agent operating in a complex environment, what are the key determinants of success? In the corporate world we can best think of intelligent agents
as an Event-Enrich-Decision-Act-Learn cycle. First, an intelligent agent (and by extension an organisation) requires the ability to observe and capture data and events from its environment. Whether simple client interactions, data streaming in from smart devices or insight into market trends, an organisation needs the ability to accurately record its environment. The more data, the better the operating environment can be understood and the better the chances to positively influence that environment. Second, it needs the ability to process or enrich the data in order to make decisions to the benefit of the organisation. The better the ability to process data, the more beneficial the decisions that can be taken. Of course, an organisation also needs to act on its decisions, ultimately effecting a change in its environment. Finally, it needs to learn and adapt over time, in order to take into account changes in the environment and optimise its own processes and behaviours. To do the above well, organisations must excel at data processing and applied machine learning, both very fast moving areas of technological progress. Small teams in organisations also cannot compete with cloud provider economies of scale applied to the integration and management of the latest hardware and software solutions in the data processing and machine learning space. Three key challenges need to be addressed: • The ability to ingest and process data at a massive scale, enabled by big data engineering . • The ability to make the best possible decisions and take those decisions into actions, based on solid machine learning models. • The ability to provide the necessary infrastructure , software and hardware, that enables data processing and machine learning activities at scale. Given these challenges, it seems like a daunting task to survive the global automation race, let alone come out on top. Learning Machines understands these challenges. We are a big data, machine learning and cloud solutions consultancy focused on helping organisations win in the global automation race. We have implemented and are maintaining solutions for some of the largest and best-known organisations in South Africa. If you need a trusted advisor, give us a call. It is 2020. What will you make of the future? Learning Machines will be exhibiting its solutions at AI Expo Africa 2020, visit their booth to learn more ai
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SWITZERLAND: A SAFE HUB FOR AI. Switzerland’s prosperity stems from its propensity for innovation. Its leadership in the Global Innovation Index is proof of the favorable conditions that exist in Switzerland for bringing science to the market. In addition to its traditional fame for high-quality products, this country in the heart of Europe is a hub for future technologies such as artificial intelligence.
Switzerland has world-renowned universities and research institutes in the field of AI. Switzerland’s proximity to cutting-edge research is one important reason why renowned tech giants such as Google, IBM or Microsoft run their AI research from here. Thanks to its traditional strength in the area of life sciences, Switzerland also drives AI developments in healthcare, with Roche notching up 41 AI patents in 2018.
AI HUB SWITZERLAND
17.6 percent of all AI patents from Switzerland are considered “top impact”
In relation to its population, Switzerland boasts the highest number of AI patents worldwide (BAK Economics, 2019), which emphasizes its great potential for innovation. According to the Times Higher Education rankings, Switzerland is seen as leading the way in AI research since its publications are most frequently cited internationally. What’s more, most of the AI patents registered here are considered top-impact patents. This excellence in AI has attracted Google to host its biggest research operation outside of the USA in Switzerland, which includes its ‘Google Brain’ team. A key aspect of Switzerland’s efficient technology transfer is the closeness of strong research institutions, small and medium enterprises and multinationals to each other. This facilitates symbiotic relationships between these actors which are encouraged by the favorable conditions in Switzerland. There are countless examples of these, including Microsoft’s laboratory for mixed reality and AI; another is Facebook’s office that works on computer vision. Companies based in Switzerland significantly benefit from its attractiveness to international talent and unbureaucratic support from the government.
place in Europe – AI startup density in relation to population
1st place – AI patents per 1 million inhabitants
Source: EconSight, 2019; Asgard VC for Artificial Intelligence, 2017; BAK Economics, 2019
Leading research institutes are contributing heavily to making Switzerland an AI hub. Notably, the Dalle Molle Institute for Artificial Intelligence (IDSIA) has gained international recognition by developing algorithms which are now used by Google, Facebook and Apple for speech recognition. The independent research institute IDIAP has been examining IT and AI topics with a vision of “promoting quality of life through scientific progress made in human and media computing”. The federally funded research institute and university EPFL is also a global leader in innovation. It is working on brain research with a focus on technology transfer, in which industry and universities work together side by side.
Robotics Personalized Health
SWITZERLAND – WHERE ARTIFICIAL INTELLIGENCE MEETS DATA SAFETY Collaboration with excellent AI research institutes, highly specialized talent pool, political stability – these are some of the reasons why innovative companies in search of a new business location choose Switzerland! Switzerland Global Enterprise is the official Swiss organization for investment promotion. Our office in South Africa would be happy to provide support for your international expansion project – free of charge: s-ge.com/sbhsa-ai Learn more about Switzerland as an AI hub s-ge.com/ai-sa s-ge.com/ai-sa
HUAWEI CLOUD – Building Inclusive AI
Developing the digital economy should be a key driver of economic transformation in South Africa. Within this context, AI and digitisation offer untold benefits for almost every sector, helping enterprises build relevant, game-changing offerings for their customers and society, reducing costs and revolutionising their services.
VISIT HUAWEI CLOUD’S EBOOTH AT AI EXPO AFRICA
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HUAWEI CLOUD can help to realise the vision for South Africa’s digital economy as a foundation for inclusive growth and social upliftment. We envisage an AI future where computing power is readily available, like the air we breathe, unleashing the full, transformative potential of algorithms. HUAWEI CLOUD AI has applications in transportation, logistics, resource management, online education, and retail. It can materially transform mobility, urban planning, farming, mining and several other industries. We have lowered the threshold for entering the AI arena, allowing industry experts to access the productivity benefits of AI, without any of the technology complexity. AI is no longer just an IT capability – it’s an operational requirement.
HUAWEI CLOUD AI allows organisations to: • Boost efficiency on repetitive, high-volume work • Transfer specialist expertise quickly and seamlessly • Go beyond human intelligence, collaborating across multiple domains The application potential of cloud-enabled AI to solve business problems is limited only by the human imagination. Thanks to Huawei’s integration across the value chain, from our Ascend chips to equipment to services to storage, we are able to offer affordable AI with the capability embedded at every stage. Our solution architects work directly with customers, training and advising free of charge to build proof of concept and proof of value in solving business problems. We don’t charge until we know what success looks like and we achieve it. The mass adoption of AI across sectors is likely to be the transformative moment that allows business to achieve its full potential as a social driver, enabling seamless delivery of services for maximum impact. We see a new business era emerging where AI is pervasive, where intelligent twins guide enterprise planning, intelligent recognition and prediction engines support applications, and decision-making optimisation engines ensure we make the right calls. Thanks to Huawei’s significant investments in building the data centres, the cloud capabilities can support any industry’s expansion into the AI space with one point of contact. Hyperscale computing with multiple vendors is no longer a business necessity. Tech is now a commodity, and the business focus has shifted from capex to opex, as the move to the cloud alleviates complexity. Businesses can now use AI to target their precise enterprise
by Michael Langeveld, VP of HUAWEI CLOUD Africa Region
intelligence needs without any long-term capital requirement. It’s about consuming the service without any of the equipment outlay. For example, the AI capabilities embedded in our cameras allow facial recognition and other AI functionality at source, processing and interpreting data, and alleviating data load through the cloud for faster result rates and business effectiveness. HUAWEI CLOUD offers infrastructure as a service, platform as a service and software as a service, with products tailored to leverage all of these for optimal enterprise intelligence. We ensure successful AI implementation by providing clear business scenarios; readily available computing power; continuously evolving AI services; organisation and talent. AI on HUAWEI CLOUD offers great opportunities to democratise business. With affordable, accessible “freemium” offerings, and training integrated into product, barriers to entry are crumbling – empowering SMEs to compete in established industries. For the public sector, the delivery of services can be revolutionised through the power of data. AI is also now a low-risk technology. Potential customers can access free cloud assets to learn, experiment, build use cases and assess their needs, with full Huawei engineering support.
About HUAWEI CLOUD
HUAWEI CLOUD now distills 30+ years of accumulated technology, innovation, and expertise in the ICT infrastructure field to offer customers everything as a service. You can grow your enterprise in the best environment with stable, secure, and ever-improving HUAWEI CLOUD services and affordable, inclusive AI. HUAWEI CLOUD provides a powerful computing platform and easy-to-use development platform to support Huawei’s full-stack, all-scenario AI strategy. By the end of 2019, HUAWEI CLOUD had launched 200+ cloud services and 190+ solutions. News agencies, social media platforms, law enforcement, automobile manufacturers, gene sequencing organisations, financial institutions, and a long list of other industry customers are all benefiting in significant ways from HUAWEI CLOUD. 3500 applications were added to the HUAWEI CLOUD marketplace with offerings from more than 10000 business partners. Web: https://www.huaweicloud.com/intl/en-us/ For more information, please visit Huawei online at www.huawei.com or follow us on: http://www.huawei.com/za/ ai
HUAWEI INTELLIGENT Transport System Rolls out in Kenya Kenya’s capital city Nairobi — or the Green City in the Sun as it is affectionately known — is infamous for its traffic jams, which in 2012 saw the city named alongside Kampala (Uganda) as one of the 10-most gridlocked cities in the world.
THANKS TO 4IR technologies like 5G, AI and the cloud, that may be about to change, In June, Kenyan publication Business Daily reported that Chinese tech giant Huawei piloted its Intelligent Transport System (ITS) in the city in partnership with the Kenya Urban Roads Authority (KURA). The solution, which is designed to focus on three service scenarios — namely traffic law enforcement, vehicle check and control, and traffic management — uses a combination of smart cameras, variable timing traffic lights, AI and big data to optimise signal light control and guide traffic. Huawei Kenya CEO Stone He told Business Daily that the system had been implemented on the Western Ring Road from Yaya Centre through to Kileleshwa Ring Road, extending to Waiyaki Way. The system is managed from a control centre at KURA’s
Nairobi traffic jam,
(Jeff Turner via Flickr CC By 2.0)
office in Barabara Plaza. The system is capable of real-time traffic monitoring. Through its algorithms and connected smart traffic lights it can enable traffic flow from roads experiencing higher traffic flows. Kenya’s Transport Cabinet Secretary James Macharia told Business Daily that the ITS had not only met the government’s expectations, but that there are plans to extend the system to other parts of the city. “The pilot has matched our expectations in terms of costbenefit analysis and we now have the confidence to go to the next level. From the pilot, we shall be scaling up to more junctions across the city,” said Macharia. Huawei held the launch of its Intelligent Traffic Management Solution in July online. The system has so far been implemented in Yanbu, Saudi Arabia and Lahore, Pakistan. Check out this Youtube video of the launch to learn more.
HUAWEI CLOUD Inclusive AI Making Intelligence Per vasive
VILLGRO KENYA INVESTS $50K in The Pathology Network Nairobi-based early-stage incubator and impact investor Villgro Kenya in May announced a $50 000 investment in Kenyan medtech startup The Pathology Network
FOUNDED IN 2017 by anatomical pathologist and CEO Dr Joshua Kibera, The Pathology Network custom support systems for pathology and laboratory medicine. The startup has developed ALIS-trn, an online lab information system and lab test referral platform. In addition, The Pathology Network provides pathology laboratories with an artificial intelligence (AI) powered cloud-based lab information system which doubles as a communication platform – connecting these labs with their clients. Villgro Kenya supports healthtech and medtech startups operating in the East African region. It said in a statement on its website that Kenya is estimated to have over 47 000 new cancer cases and 33 000 cancer-related deaths annually, with a limited number of cancer diagnosis centres and pathologists
translating to delays in diagnosing cancer early enough for treatment. By linking small labs to specialised labs for seamless tests referral with access to specialists remotely to shorten the turn around time for diagnosis, The Pathology Network promotes early medical intervention for prevention and treatment. Small labs use the startup’s platform to refer their specimens to specialised regional labs for processing and slide digitisation in preparation for a pathologist to diagnose and report on the cases remotely. Dr Kibera described said the investment by Villgro Kenya was catalytic, adding that The Pathology Network will greatly benefit from the technical assistance and business coaching offered by the Villgro Kenya team. ai
Pick n Pay implements machine learning to give shoppers personalised discounts South African supermarket chain store Pick n Pay announced in July that it will start using advanced machine learning techniques to give each of its Smart Shoppers eight personalised discounts every two weeks.
PICK N PAY said in a statement to Synapse that it will, starting 14 July, automatically load personalised discounts directly onto its customer’s loyalty card, a move it said is expected to help more customers save more on their grocery shop. The discounts, it explained, are unique to each customer and offer cash-off savings, discounts or boosted points for products that they buy most often. “This algorithm predicts what a customer is likely to buy and helps us work in conjunction with our partners to give customers personalised savings on the items they want or plan to buy,” said John Bradshaw, retail executive: marketing at Pick n Pay.
In the past, customers had to activate their personalised discounts. With the new system, customers will need to ensure they have given permission to be contacted. In addition, customers will be able to update theirs personal preference via the Pick n Pay app, website, or at a kiosk. Pick n Pay said Smart Shoppers who have opted in for communication will notice the discounts automatically applied and visible on their till slip when they swipe their card. The company said Smart Shoppers were issued over R4.0billion in personalised vouchers last year, and redemptions of these vouchers have increased year-on-year since it was launched in March 2017 after customers asked for more immediate savings on everyday items. Bradshaw said the future of loyalty programmes lies in offering real value in the most seamless way possible. “All Smart Shoppers are earning and spending their points but many weren’t reaping the full rewards of the programme by not regularly loading the personalised discounts. This improvement will instantly help put money back in customer’s pockets at a time when budgets are under pressure,” he added. ai
RISK INSIGHTS LAUNCHES SA’S ﬁrst A -de eloped ... Sustainability Rating Tool Johannesburg-based risk management advisory and consultancy Risk Insights in late May launched South Africa’s first Environmental, Social and Governance ratings tool, ESG GPS. Dr Anushka Bogdanov, founder and managing director, Risk Insights
Egyptian edtech platform Zedny launches with $1.2m pre-seed investment round
Zedny, a Cairo-based Arabic learning and development platform launched in June with a pre-seed investment round of $1.2-million.
THE PLATFORM — which has over 200 online courses, 400 animated video summaries of global business bestsellers, and over 5000 hours of educational content — uses artificial intelligence (AI) to customise the learning journey. Zedny is aimed at individuals and employers in Egypt and the Arab world who are looking to develop their business and soft skills, as well as those looking for tips to get hired or promoted. The platform provides a year-long
online learning and development at a fraction of the cost of one offline training course for an employee, and can act as an external employee performance evaluator through its AI integrations. In addition, the platform also integrates gamification into the HR development cycle to empower individuals to reach their full potential in the job market and continuously develop their skills and business acumen. ai
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consideration in borrowing and investor decisions, in an effort to prevent systemic risk,” she added. Bogdanov noted that the ratings are fully transparent and that companies can and should continue working on all sections in the model to improve their ratings. “By having an ESG rating, companies and asset managers are able to access sustainable impact funds growing worldwide at an exponential rate.” she added. The Risk Insights model, she believes, is “ripe for the time”. “The new-generation investor is not just looking at shareholder return, but also stakeholder return. This is reflected in how sustainable impact funds and green bonds have increased in volume and growth around the world. “The ESG GPS product will assist fund managers in accessing these funds. It’s now acknowledged that companies that have inclusive and meaningful social strategies – and responsibly include factors like race, gender, age and workable plans to deal with big issues like climate change and societal conflict – will be more successful in the future,” said Bogdanov. She further believes that all corporate entities are currently being impacted by these factors, and that valuation and risk will be priced up or down if responsible actions aren’t taken into account. ai
RISK INSIGHTS said in a statement announcing the launch of ESG GPS that the product is aimed principally at asset managers, development-finance institutions, banks and listed companies, all of whom need to augment ongoing valuations and expected losses, particularly in the COVID-19 influenced investment climate. The model – which is accessed through a subscription – also assists regulators with an ongoing understanding of crucial ESG factors that drive responsible governance and systemic risk. Two years in the making, the Risk Insights ESG model was conceptualised and developed by founder and managing director Dr Anushka Bogdanov – who has 26 years of international risk-management experience and holds a Phd in International Financial Management – and a team of young data scientists. Bogdanov said the model was built “specifically for South Africa”, pointing out that its key advantage is that it takes into account the country’s unique operating and investing landscape. “Our system also runs vital peer assessments, which are constantly needed in specific sectors. We have, unlike other international models, also rated an entire bourse in a single exercise. Given several massive corporate failures over the past decade through serious governance breaches, it’s clear that ESG criteria are critically important and need to be taken into
Tech Giant HUAWEI CLOUD joins
AI Expo Africa 2020 as Headline Partner HUAWEI CLOUD has joined AI Expo Africa 2020 as a headline partner. The annual event is Africa’s largest artificial intelligence (AI), data science and Robotic Process Automation (RPA) trade-focused show and conference. The third edition of the expo, which will be held as a virtual event this year, will take place on 3 and 4 September.
BESIDES MAKING the show more inclusive, the new format will make it easier for African startups and innovators to join the event along with European, US, Middle East and Asian companies seeking to enter the African market and unlock new customers and distribution partners. HUAWEI CLOUD has more 30 years of technological know-how, innovation and expertise in ICT infrastructure. With over 200+ cloud services across 18 categories, the firm’s affordable and inclusive AI services enable enterprises to grow in a stable, secure and progressive environment. The tech giant spans many availability zones within geographic regions around the world, with global data centres in Johannesburg, Bankgok, Singapore, Sao Paolo, Buenos Aires, Lima, Santiago, Mexico City, as well as in China. Its recent successes in the AI field include
the implementation of a new automated traffic system to ease congestion in Nairobi, Kenya. HUAWEI CLOUD has also developed more than 60 general purpose solutions such as SAP, HPC, IoT, security, DevOps and OPv6, and over 80 industryspecific solutions for various sectors like manufacturing, e-commerce, gaming finance, Internet of Things (IoT) as well as Internet of Vehicles (IoV). In addition, HUAWEI CLOUD provides a powerful computing platform and easy-to-use development platform to support Huawei’s full-stack, all-scenario AI strategy. HUAWEI CLOUD is the latest in a string of international firms and organisations that have signed up as as sponsors and will be exhibiting at AI Expo Africa 2020. These include UK-based RPA pioneer Blue Prism, and US-based cloud customer experience market leader Genesys. ai
UKZN RESEARCHERS AMONG GLOBAL
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Team that Introduced new Method for ML Classifications in Quantum Computing
A team of quantum information researchers made up of scientists from the University of KwaZulu-Natal (UKZN), Data Cybernetics in Germany and the Korea Advanced Institute of Science and Technology (KAIST) in July introduced a new method for machine-learning classifications in quantum computing.
PHYS.ORG reported in an article in early July that the research team, which was led Professor June-too Kevin Rhee from KAIST’s School of Electrical Engineering had proposed a quantum classifier based on quantum state fidelity by using a different initial state and replacing the Hadamard classification with a swap test. This method, Phys.org explained, is expected to significantly enhance the classification tasks when the training dataset is small, by exploiting the quantum advantage in finding non-linear features in a large feature space. The new method provides new insights for improving the accuracy of quantum machine learning.
Read more about the new method in this paper: Quantum classifier with tailored quantum kernel ai
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Artificial Intelligence has some real attention grabbing and headline worthy applications out in the wild. From drones automatically spotting sharks or swimmers in distress to fully self-driving cars, an AI generated painting that sold for more than 6 million Rand on auction and breakthroughs in AI driven drug discovery. By Marais Neethling, Principle AI Practice, Synthesis Software Technologies
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HOWEVER, SOME of the more mundane tasks that human personnel need to deal with on a day to-day basis is set for a revolutionary transformation thanks to AI. Imagine having to read hundreds of emails from clients every day, all of them pertaining to a small set of possible matters, and then creating a service task on another back-office system for each ticket so that the appropriate team can handle the query and respond to the client. This link between the business inbox and the backoffice system is crucial to the organisation, missing an email or delaying the creation of a task results in a bad customer experience. Yet this crucial link in the business process is subject to the vagaries of human nature: Boredom from repetitive tasks, sickness and absenteeism of subject matter experts and plain wrong classifications of emails.
This is a business process ripe for revolutionising. Repetitive tasks that engages System 1 thinking (characterised by Daniel Kahneman as the fast, instinctive and emotional type of thinking), in humans are ideal candidates to be automated. Thus freeing up humans to do more meaningful, valuable work and allowing machines to speed up the task and work (almost) without fail on the repetitive task. Synthesis solved exactly this problem faced by one of our customers. As a long-term and short-term insurance company, the client receives a lot of emails, through a dedicated email inbox, relating to claims, policies, new business and service providers. Each of these types of customer requests are handled by a different team inside the business. The approach we took was not just to throw machine learning classifiers at the data to see what happens. Special consideration was given to the business process and how the machine could augment the humans in their current task of sorting emails and uploading tasks to the back office system. Despite the promise of AI, machines are not 100% accurate on these jobs either. One needs to recognise that shortcoming
and build fault tolerance into the business process. The solution took the form of a bespoke line of business front end application dedicated to the classification of emails and their attachments. Emails are classified according to the team it needs to be dispatched to as well as the intent of the writer. This could for example be an email that needs to go to the claims department because the intent is to lodge a new claim. Each attachment is also classified according to the type of document it is, for example a quote or invoice or claim form. The bespoke UI in the application serves a few important goals: • Operators can see the queue of emails waiting to be classified and share the workload • It brings together data from various systems into one interface to speed up decision making and finalisation of the task by up to 600% • Collection of ground truth data for the machine learning models With this setup, even without the help of machine learning models, the humans were able to speed up the process of turning the emails into service tasks up to 11 times faster. Once sufficient training data was collected, we started on the iterative process of building classifiers for the various tasks. For document classification, we tried text extraction and classifications using text-based models as well as vision-based approaches using deep neural nets. Both approaches have their strengths and weaknesses. For example text-based models need good and accurate text extraction to be effective. But it has high accuracy on documents where the text could be extracted. For the text based classifiers, we started with a simple bag of words models. Features were extracted using TF-IDF or “Term Frequency – Inverse Document Frequency” and LDA (Latent Dirichlet allocation) and classified using various classifier models. This approach yielded surprisingly good results for certain classes and was acceptably accurate for automating a large portion of the inbound email process. No humans needed. As we continue to bring on board more email inboxes onto the platform, we are also exploring more advanced language models for use in extracting the writer’s intent and understanding what the email writer is trying to accomplish. This will undoubtedly lead to better customer service and satisfaction levels in the long term. Synthesis Software Technologies will be exhibiting its solutions and products at AI Expo Africa 2020, visit their booth to lear more. Also join Marais Neethling for a talk titled “Sorting & Categorising Email To Improve Client Service” ai
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Absa Group needed to identify and remove 40 000 Barclays artefacts from all its documents. In just eight weeks, Synthesis developed a solution powered by ML that could analyse 5 000 records in just 30 minutes.
Nedbank Insurance partnered with Synthesis, using ML and design thinking to ensure the right mails get to the right person. A robot now routes emails 24/7 to make sure that clients get a quick response, clearing up the inbox 7.5 times faster.
Synthesis and one of South Africaâ€™s largest banks introduced personalisation. This ensures the right person receives the right message at the right time. Mortgage bond products will be offered at the exact time that the client is in the market.
TSHIMOLOGONG LAUNCHES a programme to help grow female-owned tech businesses
3RD QUARTER 2020
Wits University’s Tshimologong Digital Innovation Precinct kicks off its inaugural Ya Basadi in 4IR programme, with the financial support of J.P. Morgan. Ya Basadi, meaning ‘for women’ in Setswana, is an acceleration programme that will enable Tshimologong to support established small businesses in transitioning into both technology and/or technology-enabled companies with the purpose of optimising their operations quickly and efficiently. The programme is targeting primarily women-owned businesses, which are already trading and have a clear understanding of how tech can scale their businesses. Ya Basadi will also include underserved female entrepreneurs from low income backgrounds.
KHWEZI FUDU Cenenda, Enterprise Development Manager at Tshimologong says the Ya Basadi programme taking place this month is well timed as the country dedicates the month of August to saluting women: “Entrepreneurship is fast becoming a chosen way to counteract the low economic growth and increasing unemployment. This is particularly prevalent when looking at the Small Enterprise Development Agency (SEDA) research, which notes that 72% of micro-enterprises and 40% of small enterprises are currently owned by women. Unfortunately, these businesses often require funding as well as support in terms of digital transformation.” Of significance is the imminent rise of the Fourth Industrial revolution (4IR) and how this can be transitioned into each business. Developed with three main components: technology training, experiential learning through immersions in industry and the development of a Minimum Viable Product (MVP), the programme will enable participants to understand how to apply and adopt new technology into their business such as, amongst others, Machine Learning (ML), data analytics, robotics and Internet of Things (IoT), that can lead to growth with smarter data-analysis, rapid prototyping and understanding of adaptive manufacturing principles. The ultimate goal of the programme is to help women-owned businesses scale, generate more value and create employment in Johannesburg economies. Senior Country Officer for J.P. Morgan, Kevin Latter, said: “We are excited to support this innovative programme at a time in our country where small business growth is crucial. As a firm, J.P. Morgan globally focuses on supporting small business and the empowerment of women. This programme therefore fits perfectly with our global ethos. The devastating impact of Covid-19 in South Africa has made it even more important for the business sector to support the development of smaller businesses and job creation.” In addition, Cenenda says that the programme will also focus on 4IR because of the opportunities that it presents for women’s businesses and how this evolution could assist them to flourish beyond micro and small business status: “Only 13% of women graduate in STEM (Science, Technology, Engineering, and Mathematics) while only 23% hold IT jobs. This means that the potential for women to participate in 4IR is limited. Our objective with the programme is to innovate and collaborate to find new ways of increasing access for women in technology.” With a selected cohort ready to go, she says that the entrepreneurs will be challenged to develop or build a
Minimum Viable Product (MVP) that will be presented at the end of the programme. A cross section of some of the solutions that the cohort brings, includes the provision of a travelling nurse using an online booking system; automated recycling; the provision of WIFI to households in townships; offering assessments and career guidance purely through automated calendar bookings and video calls and using financial tools to protect Africa’s green assets. “The key to success will be to support women-led businesses to transition to becoming tech or tech-enabled companies and to help them move to the next level as a business. Those companies that are already classified as tech businesses will get the opportunity to deepen their use of tech. This pipeline will need to be nurtured, developed and grown, which is why we are looking to secure additional partnerships to assist in developing the programme moving forward,” says Cenenda. The year-long Ya Basadi programme will comprise of technology masterclasses in 11 areas of technology such as App and Web Development, 3D Printing, AI, Robotics, IoT, VR and Cybersecurity. In addition to this, the entrepreneurs will get practical, on the job experience in industry; learning circles for the cohort to share experiences; and will conclude with at least a MVP being developed for or by each start-up. Facebook’s Sheryl Sandberg once said, “No industry or country can reach its full potential until women reach their full potential. This is especially true of science and technology, where women with a surplus of talent still face a deficit of opportunity.” Join Tshimologong Precinct to improve the quality of opportunities for female - led businesses, and build an ecosystem of women in technology that will forever change the landscape, shaping the way forward for women and young girls. To partner with Ya Basadi and to get more information on the programme, please contact Khwezi Cenenda on khwezi@ tshimologong.joburg. ai
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ETHICAL AI As we enter the 2020s, it is interesting to look back at how life has changed over the last decade. Compared to your life in 2010, most of you reading this probably use a lot more social media, watch more streaming video, do more shopping online and, in general, are “more digital”.
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by Thavash Govender, Data & AI Specialist Lead, Microsoft
OF COURSE, this is as a result of the continued development in connectivity (4G becoming prominent, with 5G on the horizon), the capability of mobile devices, and lastly, the quiet and transparent adoption of machine learning, a form of artificial intelligence, in the services that you consume. When you shop online, for example, you are getting AI powered recommendations that make your shopping experience more pleasant and relevant. And over the last decade, many of you will have interacted with a “chatbot”, a form of AI, which hopefully answered a query of yours or helped you in some way. The difference of a decade is basically the chatbot not seeming that amazing anymore……. The term “Artificial Intelligence” was coined in the 1950s, by John McCarthy, a now famous computer scientist. When you think of artificial intelligence, you may think of HAL 9000, or the Terminator, or some other representation of it from popular culture. It wouldn’t be your fault if you did, however, as, ever since the concept came about, it was an easy fit for Sci-Fi movies, especially ones that made AI the bad guy. If John McCarthy and his colleagues simply termed the area of study “automation”, or something equally less imaginative, we probably wouldn’t have this association today. An AI like HAL 9000, the sentient computer from the movie 2001, would be considered an “Artificial General Intelligence”, one that has a general knowledge across many topics, much like a human, and can bring all of that together to almost “think”. This is opposed to a “Narrow AI” which would have a narrow specialisation - an example would be building a regression model to predict the probability of diabetes in a patient, given a few other key health and descriptive indicators. Technically you could consider this automated mathematics and stats, as the algorithms have been known for more than 100 years, but the progress is building now because the data and the computing power are more available and affordable. The AI of today is nowhere close to being an “AGI” though. Instead, the AI projects that we see
being worked on are most likely “Narrow AI” Machine Learning projects. That means that we’re safe from any Terminator (for now). However, if we don’t consider ethics as part of the AI creation and development process, even for Narrow AI, we could still unleash tremendous harm on society, even sometimes without realising it.
The broad spectrum of ethical impact from the actions of artificial intelligence range from a simple ML regression model not wanting to recommend loans to a particular demographic, all the way to a AGI being given the power to do tremendous physical damage, either intentionally or unintentionally. Further pressure on the need for the ethics debate is the pace of AI adoption, that is, over the last decade, it went very quickly from being spoken of to being real. Consider the advancements in conversational speech, image recognition and deep learning that would have been science fiction in 2010 ? In late 2019, Microsoft data scientist Buck Woody visited South Africa, to do a few events here. I asked Buck, while doing a video interview with him, on where AI adoption was going next. His answer was- “it will become transparent”, meaning that very soon, it will feel normal to have machine learning everywhere, all processes in business or our personal life having predictive capability and optimisation, not just automation. This is very similar to what happened with microcontrollers and software in the late 20th Century. We expected everything from our cars to appliances to have onboard computers or at least logic circuits, and the improved experience from the device being due to decisions being made in some form of software. The improvement very quickly became the norm. Expect a similar on-ramp of AI, as more pieces of our lives become “AI powered”.
Building for Ethics
Given the expected adoption. experts are now saying
The most prominent danger of AI, that is highlighted fairly often, is the issue of bias, the danger that AI systems may not treat everyone in a fair and balanced manner. For example, when AI systems provide guidance on medical treatment, loan applications or employment, they should make the same recommendations for everyone with similar symptoms, financial circumstances or professional qualifications. Theoretically, since AI systems take data and look for actual patterns and facts, the outputs should be perfectly accurate. However, the problem is that todays AI systems are being designed by humans, and there are two ways bias can creep in : 1) The inherent and perhaps unconscious bias of the designer 2) Flaws and bias in the data used to create and train models Lets use the example of a system designed to help HR recruit software developers. In the current world, we may have a situation that most software developers are male, even though we would like to change that to a
Safety and Reliability
While the majority of AI systems today involve analysing data and making a prediction or defining a trend, this will change rapidly in the early years of the decade. As the outputs of AI are increasingly used to effect the physical world, a focus on safety and reliability becomes critical. This is similar to the journey the software world went through a few decades back. A clear example of this would be autonomous driving systems. In recent years, one manufacturer of cars has offered an AI powered autonomous driving option on their vehicles, however a spate of accidents brought the technology into question. This is where the ethical design of AI is non-debatable - even one more death in an accident ( if the system did have a flaw ) is unacceptable. From an ethics perspective the questions are - was the system ready for release ? Should the system be pulled
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more equal distribution. An AI system, however, may be trained on current data and include bias towards males in its recommendations. Ethical AI requires that anyone developing AI systems be aware of the above issues, and take steps to ensure that both accurate, neutral data be used as inputs, as well as using methods to eliminate other bias in the creation process. Techniques like peer reviews and statistical data assessments will be needed. Be aware that the above isn’t the end of it, though. It has been found in multiple cases that AI sometimes allows some form of bias to creep back in over time, so post deployment the system will have to be continuously monitored. This is where “MLOps” comes in, an emerging field that is focused on the lifecycle of model development and usage, and in particular, aspects of machine learning model deployment. MLOps will have to include bias detection as part of model degradation analysis, to deliver ethical AI.
that we should build AI more cautiously, and it is extremely important that we build with ethics in mind, from day one. When we had the microcomputer revolution in the 1970s , was ethics considered ? Perhaps not, there was nothing to link ethics to processing of data, even though the software systems built on top of those needed to consider ethics. When we had the internet revolution of the 1990s , and the mobile phone revolution of the 2000s, the question wasn’t explicitly being asked either. But perhaps it should have been, given the issues that we now see around privacy and social media influence on major events. The public trust in AI, if ever lost, will be very difficult to regain. With this in mind, Satya Nadella, CEO of Microsoft, proposed in June 2016, five principles to guide AI design. There are : 1) A.I must be designed to Assist Humanity 2) AI must maximise efficiencies without destroying the dignity of people 3) AI must be transparent 4) Have accountability so that humans can undo unintended harm 5) Have intelligent privacy and data protection built in to guard against bias So what are the dangers of AI that we need to protect society against ? As you might have imagined, let’s not focus on “doomsday” scenarios with AGI’s running amok - firstly, we are nowhere near that possibility in 2020. Secondly, and more importantly, there is a tremendous amount of harm that can be done to society just with the incorrect implementation of “narrow” AI’s, as explored in the following sections.
Ethical AI from production even if the accident rate is low ( given the risk ) ? Sometimes the ethical questions could come post design / engineering and after production.
If there’s a hot topic in the tech world at the moment - it would be privacy. In recent years laws have been put in place globally to ensure that the personal information of individuals is protected and not collected unscrupulously. While this is preferable, it is something of a double edged sword for the world of AI - as you know, AI needs data, and lots of it, to be as accurate and useful as possible. A particular quandary would be if society needed to collect private information from individuals, in order to deliver an AI system that serves society in some form - where would the world draw the line ? This is exactly what happened early in 2020 with the COVID-19 pandemic. In order to measure whether social distancing, critical to stopping the spread of the virus, was indeed taking place at an acceptable rate, various social distancing applications entered the market. Of course, these would collect a lot of information on an individuals cellphone, including precise location information and history. Many chose not to install these applications, also known as contact-tracing apps, however governments, desperate for this information to see if social distancing measures were in fact working,
were conflicted about them. If the issues around data privacy aren’t sorted out in the current timeframe, the danger is that the public trust would be lost, and both individuals and organisations may not be inclined to share data that is needed to build the useful AI systems of the future. Even if there is future agreement on the collection of data for use in AI, ethical AI will demand frameworks in place on how that data is used, as well as transparency. There are already techniques being used by companies like Microsoft to protect the privacy of individuals where their data is being used, such as differential privacy, homomorphic encryption, and many others.
As AI systems become more common place and make increasingly important decisions that impact society, it is critical that we understand how those decisions are made. The current consensus is that an AI system should provide clarity on all aspects of its creation, from the data used in training through to the algorithms itself. To simplify, the question that should always be asked is - “Do I really understand why this particular model is predicting the way it is?”. Even experts can be fooled by a model with an inbuilt flaw. There have been developments in this space however. One such is the concept of “model
An AI like HAL 9000, the sentient computer from the movie 2001: A
Space Odyssey, would be considered an “Artificial General Intelligence”
This brings together the technologies mentioned like InterpretML to create a framework that can help organisations. Lastly, we have to consider ethics outside of model development, but in model usage. Those who use AI systems should be transparent about when, why, and how they choose to deploy these systems. Consider the
impact of AI to the jobs market - it is clear at this stage that over the next decade increased automation, aided by artificial intelligence technologies, will impact the job market. We are already starting to see visible examples of this - in 2019 a famous restaurant chain implemented a system where a customer could walk into a store and place an order at an automated kiosk. Technologies like speech recognition aid automation making such scenarios possible. The ethics decisions will be - should a company implement such ai-assisted automation at the cost of jobs, especially where the economic benefits aren’t clear ? Luckily, it is also expected that AI will create jobs as well. Some examples include data scientists and robotic engineers, and perhaps roles that we cannot imagine yet. In fact, AI will probably reduce the number of low-value, repetitive, and, in many cases, dangerous tasks. This will provide the opportunities for millions of workers to do more productive and satisfying work, higher up on the value chain, as long as governments and institutions invest in their workers education and training.
We live in exciting times, as this generation will be the first to witness AI will playing a greater role in our daily lives. As mentioned, technologies like speech and face recognition were sci-fi ten years ago, and its exciting to imagine things, that seem sci-fi today, which will be real and common place by 2030. Imagine working remotely via a Hololens device, meeting with people all around the world, with your speech being translated instantly for people on the other side, while your AI assistant tracks the meeting progress in the background and send outs notes. This is the tip of the iceberg, and yet, this reality will be threatened if the trust in AI is lost - all the issues like privacy and security need to be proven to have been sorted out before large scale adoption like this happens. There is still enough time for this to be achieved though, with enough cooperation between organisations and governments. Going forward, AI will only become more complex. Just as with the journey with software, if design patterns, standards, and methodologies enabling development aren’t laid out early on, we may see many failed projects, which would stall innovation, however the risks of not considering ethics as well will be more catastrophic. Everyone involved in AI in any way has a role to play, to make sure that this exciting frontier is implemented with ethics in mind, so that we reap as many of the benefits as possible as a society. ai
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interpretability”, which is now being serviced via frameworks like InterpretML ( which is being referenced by most ML platforms including Azure ML). Model Interpretability allows data scientists to explain their models to stakeholders, confirm regulatory compliance and allow further fine tuning and debugging. There is also the Fairlearn toolkit, being referenced by tools like Azure ML now, which would allow you determine the overall fairness of a model. This is quite useful. To revisit the examples earlier, a model for granting loans or for hiring could be referenced for fairness across gender or other categories. This isn’t really optional anymore - in many industries, regulators are now asking to see proof that these best practices were followed in building these models. It is also important that we show accountability - the people who design and deploy AI systems must be accountable for how their systems operate. While AI vendors can provide guidance on model transparency, accountability needs to come from within - organisations will need to create internal mechanisms to ensure this accountability. An example of how vendors are trying to bring all of this together is the Responsible ML initiative. The goal here is to empower data scientists and developers to understand ML models, protect people and their data, and control the end-to-end ML process.
UN ECONOMIC COMMISSION
of Africa partners with telcos
on COVID-19 Communication Platform
3RD QUARTER 2020
“This is the first time a mobile USSD platform has been interactively paired with big data AI to yield insights which neither alone could achieve,” UN Economic Commission of Africa.
IN RESPONSE to the COVID-19 pandemic, the UN Economic Commission of Africa (ECA) has partnered with mobile network operators to provide a mobilebased public communications platform which will provide more than 600 million users across Africa with the latest public health advice. The platform’s mandate was jointly agreed on by the World Bank, International Telecommunication Union, GSMA and the World Economic Forum in April (see this pdf). ECA said in a statement on its website in June that the Africa Communication and Information Platform (ACIP) will also provide national and regional COVID task forces with user generated survey data and actionable health and economic insights. By improving national data and statistics, ACIP will enable authorities to better analyse pandemic related problems and implement appropriate responses. The platform – which was launched on 23 June – will also allow COVID19 task forces to deploy health and economic resources to mitigate the pandemic’s impact. The free to use service was developed by the ECA in collaboration with four major mobile network operators including MTN – a technical partner on the initiative – and a data integrator. The other telcos taking part in the initiative include Airtel, Ethio Telecom, Orange, Vodafone, Vodacom, and Safaricom. ACIP harnesses mobile narrowband channels using a combination of text (USSD) and voice interactions (IVR). On the broadband side, the platform uses public data from digital channels, including online and social media. By using mobile narrowband and broadband, the platform can reach 3G/smartphone users and mobile subscribers with earlier generation 2G handsets, also known as feature phones. The rollout of Phase One, which started on 23 June, will
cover mobile users across more than 23 countries, representing more than 80% of Africa’s total mobile subscribers. Users will be able to access locally relevant health advisories and medical advice including a symptom checker. ECA explained that anonymised user inputs, including survey responses, will be fed to an artificial intelligence (AI) driven system. This integrator will build data dashboards and actionable insights for national and regional level policy makers. These may include identification of emerging virus hotspots and shifts in public sentiment (via survey data and social listening). The integrator can also provide smart alerts for anomalies detected by the AI. ECA pointed out that all information on the platform is for use at the national authority level and for national COVID task forces, as well as for ministries of health and finance. In addition, the commission added, national authorities will retain control over data provided by their own users and decide what information is made available to their national users. ECA said this is the first time a mobile USSD platform has been interactively paired with big data AI to yield insights which neither alone could achieve. Under Phase Two, which ECA said will be launched in a few month’s time, the service will encompass an additional 20 percent of African mobile users and expand to include economic and humanitarian-focused communication. National authorities will be able to conduct community level messaging for social welfare, including for example facilitate cash distribution (including e-payments); send targeted information on local food distribution or clean water provision. When data reveals emerging virus hotspots, authorities would be able to direct medical resources to the affected areas and alert local inhabitants to their availability. ai
HSRC, FACEBOOK LAUNCH
ethics and human rights in AI research initiative
The Human Science Research Council (HSRC) of South Africa in July announced a request for proposals (RFP) â€” in partnership with Facebook â€” that will result in the production of papers on artificial intelligence (AI) from academic institutions, think tanks, and registered organisations operating across Africa.
Policy makers are emphasising the need for ethics by design. What does ethics and AI mean and look like in an African context? How can academia, government, and industry collaborate to promote and advance ethics by design practices and frameworks? How can developers and companies ensure that their AI systems are explainable, what their purpose is, and what they entail? How can academia help companies and governments better understand and operationalise ethics within their own sectors and activities? How can academia both inspire and build on industry best practices for responsible and ethical development of AI? How can developers and companies ensure that their AI systems and applications are built in a fair and unbiased way? How should social science and humanities questions around fairness and discrimination be embedded into the technical design of AI? What best practices can we advance in this space? How can developers and companies ensure that their AI systems are transparent to the affected individuals in a meaningful way? (For example, how will a person know whether they are being unfairly discriminated against because of an automated decision?)
Governance, Ethics and Human Rights
How do hard and binding legal instruments, namely existing and proposed legislation, and ethical AI governance frameworks (soft law, non-binding) interact and mutually influence each other? Does the former stem from or pre-empt the latter? Are they complementary or competing? How should international, regional and national human rights frameworks coexist and interact with each other? What can AI and ethics learn from human rights law and from the obligations it places on public and private actors? What is the role of ethical codes in the broader regulatory landscape? How should they relate to laws and regulations (either existing or being developed)? What is the role of academia in 1) promoting research on AI governance frameworks; 2) analysing, anticipating, and identifying gaps in legislation and other governance models related to AI development and use; and 3) articulating best practices to guide ethical and innovative uses of data?
AI Ethics and Diversity
What factors should inform human and technical diversity in the design and development of AI systems (e.g. linguistic diversity, diversity of race, gender, religion etc) in the African context? How should AI developers and companies foster and apply a multicultural approach to the ethical design of AI? Continued on page 48
3RD QUARTER 2020
Ethics by Design
What level of autonomy should be provided to the affected individuals concerning the use of AI without compromising the legitimate purposes of AI, and how should individuals exercise control over automated decisions?
THE HSRC said in statement on its website that the research initiative complements Facebookâ€™s existing efforts to bolster independent research currently underway in Asia Pacific, India, Latin America and at the TUM Institute for Ethics in AI. The HSRC said it is interested in research proposals that pertain to three topics, namely:
Getting innovation right
in South Africa
3RD QUARTER 2020
Local organisations see digital transformation as a key enabler of innovation, but to realise the real benefits they must consider their approach carefully, argues Lahini Sivaganeshan, Agile Solutions Consultant at Oracle.
DIGITAL TRANSFORMATION (DX) and innovation are often treated as separate initiatives whereas, in reality, they are inextricably intertwined. The subtle dynamics need to be understood, especially now as organisations are putting their DX programmes into fast forward in the wake of the Covid-19 pandemic and the massive changes it has initiated, Sivaganeshan says. “The more digitalised companies were, the better able they were to adjust to this new world. But CIOs have also realised that DX has to be seen as part of an innovation journey that will enable organisational agility—the all-important ability to read market changes and adapt to them at speed,” she says. Central to any discussion about DX and innovation is the question of data. Data has emerged as the crown jewels of the corporate treasury, the raw material for the insights that underpin innovation. Research by World Worx in partnership with Cisco shows that large enterprises in South Africa generally see DX as a key strategy in dealing with Covid-19 and the associated crisis. Yet, says the report, only a third had fully digitalised before the pandemic hit. Another study of Sub-Saharan Africa by the International Data Corporation showed that 57% of organisations are putting their DX programmes on the fast track. This sense of urgency contains a danger: organisations must not cut corners when it comes to how DX and innovation generally are structured. “Organisations must never lose sight of the basic fact that DX and innovation are not ends in themselves: they are enablers of business strategy. The starting point should be the business problem, how urgent it is and how impactful it will be,” says Sivaganeshan. “Then one must interrogate the current business model and consider how it needs to be changed as part of the DX/ innovation process. The technology solution must be guided by this work.”
Aligning business and IT
Another important precondition for success is collaboration between IT and the business. For years, the CIO has been the go-to person for innovation and DX, but closer integration between the lines of business and IT is vital. Finance, HR, sales and marketing must become more involved. At present, says the IDC, only 12% of respondents can say that IT and other business lines collaborate closely to develop the DX and
innovation road map together. “When DX is aligned with the business and what it needs to do, one starts to see really exciting innovations that use advanced data analytics to take the business to a new level,” Sivaganeshan says. For example, Oracle is working closely with the World Bee Project using artificial intelligence to analyse data from sensors and other sources to enable apiarists to make informed decisions quickly, and help make hives healthier and more productive. “In this way, Oracle is helping address the challenge of food security and protecting farmers’ livelihoods,” notes Sivaganeshan. Another example is the collaboration between Oracle and Sail GP, an international sailing competition. Each boat is equipped with up to 1 200 sensors, with the data being fed back into Oracle’s Autonomous Data Warehouse, where it is rigorously analysed. Crews use the data-based insights to complement their own expertise to make decisions quickly during the race. “This is what modern business is increasingly going to be like: harnessing technology and data to enable rapid, fact-based decision-making on the fly,” Sivaganeshan comments. “It’s about DX leading to innovation that gives real competitive edge.”
How to innovate successfully
So how to innovate successfully? Craig Nel, Oracle MEA Cloud Platform Leader, Mobility, confirms that any innovation journey must begin with a problem or a goal. He argues that the foundation for successful innovation is the triangle of people, processes and projects. “A good structure and processes are needed, as well as the right people with the right mind set and attitude. The people need to be trained and the best way to do that is to learn by doing,” he says. “One must move beyond talking by mobilising small groups to try out some innovation initiatives—and give these teams time to learn.” Other key success factors include measuring the innovation project to determine its impact and build credibility within the organisation, and finding the right partnerships. “You simply can’t do it alone: companies need to find diverse partners to make progress,” he says. “By finding the right partners, you can accelerate the transformation process to become more competitive by serving customers better.” Find out how Oracle can help you use data more innovatively to achieve your business goals ai
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FNB IS LEVERAGING AI
to redeﬁne risk management and ways of working
FNB has been harnessing artificial intelligence (AI) to re-imagine risk management and forensic due diligence processes. The result is the ability to have a more robust forensic due diligence process, review profiles for various financial crimes holistically, more rapidly, and more consistently, and free up the time of analysts to perform the functions that they remain better suited to than AI. This doesn’t mean we need fewer analysts, but rather that their focus is now being used to conduct quality assurance of reviews, and to constantly feedback data into the evolution of the AI. On average, the use of AI frees up 70% of analysts’ time, and generating a forensic synopsis ready for a human analyst to review that previously took hours can now be completed in as little as 8 seconds.
3RD QUARTER 2020
By Dr. Mark Nasila, hief na tic cer Risk
AI IS growing more prevalent in a wide range of industries, from breast cancer screening tools developed by Google, to analysing imagery captured by drones on farms to combat disease or optimise harvesting. In all instance, AI is more adept at considering large datasets. When it comes to banking, AI can serve a number of purposes, but it’s especially useful for risk management, because it’s able to consider a huge array of variables simultaneously, identify patterns of behaviour by extrapolating from massive datasets, provide insights and reviews rapidly that can then be assessed by human analysts, and — ultimately — assist with decision-making while increasing the accuracy of those decisions and reducing false positives. As a bank, FNB is required to monitor certain regulatory and financial risks, including tax evasion, money laundering, fraud, and insider trading. Traditionally, this is a timeconsuming and laborious process that requires human analysts to gather large swathes of information, review them and generate insights from them, write rationales supporting their thinking, and finally, make decisions about potential or perceived risk. With our AI-enhanced forensic due diligence process solution called “Manila”, FNB is able to meet all of those regulatory requirements, but decisions can be taken more efficiently, faster and produce outcomes with enhanced accuracy.
How Manila Works
Much like a human analyst would, Manila begins by creating a single view of the customer from across the bank. This can include data from up to 50 sources, including their spending activities and other transactional activities within FNB’s products or platforms. The AI then checks for any red flags within the organisation’s data about a customer. These include, for instance, anything to suggest a mule account, tax evasion, or links to other high-risk customers. Manila then starts putting together an insight report on the customer, which it delivers in natural language, and this information then guides the human analyst when they’re doing a review. Manila usually takes between 8 and 13 seconds to generate a forensic synopsis ready for a human analyst to review. Sometimes this process can take as long as a few minutes, depending how big the dataset being reviewed is, but that’s still hours less than it would take an analyst. Perhaps most impressive, though, is the AI’s ability to produce a written analysis and a rationale outlining behavioural evidence around financial crime. An analyst uses these to help them make the decision whether or not a certain customer is high-risk. Because the solution is so consistent in its output, there’s a 70% reduction on average from the previous time that was required to provide suitably detailed and thorough quality assurance. Continued on page 48
HOW TRUSTWORTHY IS your organisation’s AI?
What’s going on in Africa?
African countries are lagging behind when it comes to guidelines or policy around the regulation of AI. In January, the Ethiopian government announced it would establish an AI research and
development centre that would among other objectives seek to regulate the industry in the country. In February, South African president Cyril Ramaphosa —who is the current African Union chairman — called for the establishment of an Africa Artificial Intelligence Forum. It’s not yet clear whether the body will set about setting ethics guidelines for AI on the continent. In July UNESCO launched a global online consultation on the ethics of AI in a bid to give everyone around the world the opportunity to participate in the work of its international group of experts on AI. The group has been charged with producing the first draft of a Recommendation on the Ethics of AI which will be submitted to UNESCO Member Sates for adoption in November 2021. If adopted, it will be the first global normative instrument to address the developments and applications of AI. UNESCO is convinced that there’s an urgent need for a global instrument on the ethics of AI to ensure that ethical, social and political issues can be adequately addressed both in times of peace and in extraordinary situations like the current global health crisis, The UNSESCO recommendation is expected to define shared values and principles, as well as identify concrete policy measures on the ethics of AI. UNESCO said the recommendation will also help member states ensure they hold the fundamental rights of the UN Charter and of the Universal Declaration of Human Rights, and that research, design, development, and deployment of AI systems will take into account the well-being of humanity, the environment and sustainable development. ai
THE LIST, which was first presented with the Ethics Guidelines for Trustworthy AI in June 2019, was revised following a piloting process which took place between June 2019 and December 2019 that involved more than 350 stakeholders The revised list, which operationalises the key requirements for ethical AI and offers guidance to implement them in practice, has been translated into a web-based tool to support AI developers and deployers in developing Trustworthy AI. The Ethics Guidelines introduced the concept of Trustworthy AI based on seven key requirements. These are human agency and oversight; technical robustness and safety; privacy and data governance; transparency; diversity, non-discrimination and fairness; environmental and societal well-being; and accountability. The European Commission said that ALTAI will help to ensure that users benefit from AI without being exposed to unnecessary risks by indicating a set of concrete steps for selfassessment.
3RD QUARTER 2020
In July the European Commission’s High-Level Expert Group On Artificial Intelligence (AI HLEG) presented its Assessment List for Trustworthy Artificial Intelligence (ALTAI).
N is le eraging A to redeﬁne risk management... Continued from page 46 So, how does Manila achieve high levels of accuracy and competence? Because the dataset used to train is using the best reviews as inputs. The result is rationales that include descriptions of money flows and transactions, in easy-tounderstand language, with familiar formatting, and complete with any adverse media coverage of the customer, that would otherwise potentially take a human analyst many hours to source and verify.
The shifting role of human intelligence
3RD QUARTER 2020
The AI system, Manila, gathers data from multiple sources, creates a single view of a customer, and provides insights and a rationale to guide the decision-making process. The human analyst, meanwhile, provides quality assurance and the final recommendation, but now in record time. Previously, this process, when undertaken entirely by a person would take in the region of 170 minutes. With the help of AI, that process is reduced to around 40 minutes. Similarly, depending on the complexity of the customer or the request, producing a synopsis now takes a matter of seconds, rather than hours or days. The quality of the analysis and report hasn’t changed, nor has the quality of the outcomes. What’s changed is the process and how speedily a decision can be reached. And in addition to being a more rapid process, the forensic risk management process is now a more holistic and accurate one. It’s difficult for a human being to look at all risks at once to get a complete view of a customer. But this is precisely the sort of task that AI excels at.
Re-inventing risk management and ways of working
Manila isn’t merely changing the forensic process, but also ways of working for FNB. We are heeding the call of the president during the COVID-19 lockdown to enable our staff — wherever possible — to work remotely. Our AI solutions enable our analysts to do quality assurance and approvals remotely, more rapidly, all while maintaining the highest standards. We’re exploring technology to better serve customers and be more efficient, while also stimulating a culture of building solutions in-house. Not only does this approach help drive productivity, but by creating solutions rather than importing them, we develop the skills of our people, can scale solutions across different functions, and keep the economy of South Africa growing while imbuing our people with world-class abilities.
Helping protect our customers and ourselves
Better risk management also means helping protect our customers and our platforms and services. It means protecting customers as they transact and interact with other services. With remote working set to become increasingly common, our shift in culture and our ongoing efforts to constantly innovate mean we’re forever exploring better and smarter ways to maintain productivity while improving the lives of our analysts, and our customers. AI helps our analysts work smarter not harder, while maintaining quality and keeping our customers safe. Risk will always keep evolving. Our solutions and responses to it will too. ai
HSRC, Facebook launch ... Continued from page 43 What are the most prominent narratives on the role and impact of AI in Africa? How does local knowledge on the relationship between humans and machines shape the understanding, the perception and adoption of AI in Africa? How should companies navigate the tension between the benefits of a global approach versus the need to acknowledge important particularities and differences stemming from companies’ regional user base? What would be a sound and scalable methodology
for researchers and product developers to recognise and solve ethical challenges, while leveraging different regional perspectives that promote diversity? The HSRC said proposals will be reviewed by a selection committee and the entities whose proposals are selected will receive a research grant. Applications will close on 30 July, with successful awardees set to be listed on the Facebook Research website. In addition, awardees will be encouraged to openly publish any findings or insights from their work, with the research findings set to seven as the basis for discussion for a workshop that will be held in Accra, Ghana in early 2021. ai
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companies as customers
on Deloitteâ€™s Tech Fast 500
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as of September 5th, 2019
invests R100m in SA
agritech startup Aerobotics
3RD QUARTER 2020
South Africa’s Naspers announced in late May that it had, through its early-stage business funding initiative Naspers Foundry, invested a R100-million in Cape Town based agritech startup Aerobotics.
50 Left to right, Aerobotics founders James Paterson and Benji Meltzer at the Australian Macadamia Conference in 2018
THE DATA analytics startup uses aerial imagery and machine learning algorithms to optimise crop performance and predict yields for farmers in up to 18 countries including South Africa, Spain, Australia and the US. Aerobotics was founded in 2014 by CEO James Paterson and CTO Benji Meltzer. Prior to this deal, the agritech startup had raised $4.8-million across five rounds from venture capital investors that include Paper Plane Ventures, Nedbank, 4Di Capital and Savannah Fund. Commenting in Nasper’s statement announcing the deal, Paterson said the intersection of agriculture and technology has always been his passion. Paterson added that it has been incredible to work with a talented team, and leading agricultural groups, to contribute towards the future of agriculture. “We are proud to be building quality technology in South Africa and delivering it to customers around the world. Our journey is only just beginning, but alreadyAerobotics has demonstrated success in our ability to collect and analyse tree and fruit-level information, which are critical to the agricultural industry. “We have seen great support from commercial-scale farmers and, more recently, crop insurance companies in the US who require accurate tree-level information about their clients. We are excited to have Naspers as a partner, bringing proven skills in building global technology companies together with the capital required to continue building for, and with, the agricultural industry,” he added. Phuthi Mahanyele-Dabengwa, CEO South Africa of Naspers, said food security is of paramount importance in South Africa, and the Aerobotics platform provides a positive contribution towards helping to sustain it. “This importance has been highlighted further in the wake of the Covid-19 pandemic, with agriculture considered globally as critical infrastructure. This young, all South African team, has produced a world-class technology solution in South Africa and has also successfully entered the US market where they are gaining momentum. This type of tech innovation addresses societal challenges, and is exactly the type of early-stage company that Naspers Foundry looks to back,” added MahanyeleDabengwa. ai
The global AI Agenda
Some of the reports top findings include:
Interest in and uptake of AI is set to continue in the
coming years with 44% of respondents expecting AI to power between 21% and 30% of their business processes in the next three years Customer service departments — think chatbot advisers in the financial services sector and machinelearning based scoring — are most actively using AI across Africa and the Middle East. Less than a third of respondents stated that they are currently using AI to grow revenue, with sales and marketing expected to be a major growth area in the coming years. The main obstacles around AI in Africa and the Middle East revolve around change management (58%, relative to the global average of 51%) and issues around data quantity, quality and availability Check out the full report here ai
THE REPORT, which was released in June, is part of The Global Agenda, a global study of over 1000 AI experts conducted in January and February. The study examines AI adoption, leading use cases, benefits and challenges. An interesting insight from the report, which MIT Technology Review pointed out, is how the wealthier countries in the Middle East are exploring AI as part of broad economic transformation plans — moving from oil and reinvesting the surpluses into innovation — while in Africa AI efforts are more bottom-up, and often driven through partnerships with global tech companies and local startups solving social challenges like health care and food security.
3RD QUARTER 2020
Curious about how organisations in Africa and the Middle East are using AI, and more importantly how they plan to use it in the future? Then you’ll want to check out a new report by MIT Technology Review Insights — produced in association with omnichanel customer experience and contact centre solutions leader Genesys — titled The global AI Agenda: The Middle East and Africa.
GOOGLE FOR STARTUPS Accelerator Africa 2020 AI, Data Science startups selected for Google for Startups Accelerator Africa 2020
GOOGLE FOR Startups Accelerator (formerly Launchpad) in June announced the names of the 20 African startups selected for its Africa Class 5 cohort. The cohort includes startups hailing from Ethiopia, Ghana, Kenya, Nigeria, South Africa, Tunisia and Zimbabwe. The 20 companies operate across the logistics, transportation, education, agriculture, e-commerce, media and professional services. Notably, among them are a few companies using Artificial Intelligence and Data Science. These include: Curacel, a Ghanaian startup which has developed an AI-powered platform which enables insurers to track fraud and automatic claims seamlessly. Kaoun, a Tunisian startup which helps users create
free bank accounts remotely and uses facial recognition in its innovative E-Know Your Customer (KYC) system. Zuka Data Science, a Kenyan blended learning platform with engaging Data Science programmes designed by experts to enable individuals and organisations at all levels become data fluent Thumeza, a Zimbabwean next-generation logistics platform using data in order to optimise the logistics function of enterprises. The three-month programme — which kicked off on 29 June — will run until 11 September. You can check out the full list of the Google for Startups Accelerator Africa Class 5 cohort here. ai
Samurai Incubate announces investment from new fund, seeks AI ventures
3RD QUARTER 2020
Japanese venture capital (VC) firm Samurai Incubate Africa Inc in July announced the first investment from its newly launched Samurai Africa 2nd General Partnership with a deal with Nigerian startup Eden Life Inc.
THE TOKYO-BASED VC which was founded in 2018 primarily focuses on investment and support for pre-seed and seed stage startups in Africa. The VC invests average ticket sizes of between $50 000 and $500 000 in startups from Nigeria, Kenya and South Africa which operate in fintech, insurtech, logistics, healthcare, commerce, energy, agritech, mobility, and entertainment. Samurai Incubate managing partner Rena Yoneyama told Synapse that the VC is also interested in investing in startups in the AI and Data Science field. Samurai Incubate did not disclose in a statement to Synapse how much it invested in Eden Life. The Lagos-based startup provides a service which connects busy city workers with service providers who supply meals, laundry and house cleaning services. The startup recently joined an acceleration programme
conducted by US-based early stage early stage VC Village Global, which also participated in the deal. Anne Dwane, co-founder and partner at Village Global said “We’re thrilled to back the talented team at Eden. We’re impressed with their vision, velocity, and customer-focus”. Samurai Incubate Africa started investment into African startups in July 2018 and has a portfolio which includes Wallets.Africa, Complete Farmer, Bamboo, LULA, Simbapay and Mpost. The VC said the COVID-19 pandemic has made it difficult for international VCs to visit other countries and hold face-toface meetings with founders. “But Samurai Incubate Africa recognises the importance to make new investments and believes that great founders and strong companies are born in difficult times, and therefore we’ll keep investing remotely,” it added in its statement. ai
ZINDI AND AI4D BUILD
language datasets for African NLP
“The heart of this project is about creating a more inclusive AI sector. We are thrilled to host this challenge on Zindi because it means offering everyone, irrespective of their background, the chance to learn about and contribute to this growing field. This challenge allowed us to showcase the work of people across the continent that are capable of making amazing contributions — now or in the future- but may not have seen themselves as ‘qualified’ NLP researchers,” says Celina Lee, CEO of Zindi.
Looking for African NLP data
Next steps on Zindi and beyond
The challenge called on natural language processing (NLP) researchers and data scientists across Africa to develop and submit datasets for underserved or underrepresented African languages, for use in future NLP applications like automated translation or speech recognition. “We wanted to see what African NLP practitioners could do if we empowered them with the right resources,” says Kathleen Siminyu, Regional Network Coordinator for AI for Development (AI4D) Africa. “We planned to host a traditional NLP challenge on Zindi, but we realised that access to good African language datasets was a hurdle we could not ignore.”
Funding to create great NLP datasets
Between November 2019 and March 2020, Zindi received more than 40 submissions to the challenge, representing more than 30 African languages. Ten winners were selected (two per month), and AI4D has now chosen five of these to be funded as AI4D Dataset Creation Fellows. The fellows are: • Amelia Taylor (Chichewa — spoken in Malawi and Zambia) • Kevin Degila (Fongbe — spoken in Benin, Nigeria and Togo) • David Adelani (Yoruba — spoken Nigeria) • Thierno Diop (Wolof — spoken in Senegal, Gambia and Mauritania) • Hatem Haddad (Tunisian Arabizi — Arabic dialect spoken in Tunisia)
Over the next three months, the fellows will get financial and other support to develop their datasets further. They will focus on expanding data sources, ensuring that the datasets are developed with their final purpose in mind, and making sure that the data is sourced in a legal, ethical, and unbiased way. The fellows will have support from partners Knowledge 4 All and CIPIT at Strathmore University. At the same time, Zindi is pleased to be hosting a second African Language Challenge in partnership with AI4D and GIZ, where NLP practitioners from South Africa, Ghana and Uganda can submit their datasets for a chance to be included in this fellowship programme. The competition closes on 3 August. Meanwhile, the AI4D fellows and their teams will build out their datasets and work towards publishing the dataset in October 2020, along with an academic article detailing their work. Once published, these eight datasets will be put to work as NLP challenges on Zindi, and eventually help ensure that African languages are adequately represented in digital spaces. This work will also inform UNESCO AI policy and be included in UNESCO’s World Atlas of Languages platform. “Working in AI on the African continent, there is a lot of high-level optimism, which is great,” says Siminyu. “But it’s the groundwork that matters. Getting this right will mean wide exploitation, which will drive more funding and more support. This kind of work makes that optimism actually mean something.” ai
“I’M NOT a Chichewa speaker,” Taylor explains. “So one of the first things I did when I moved to Malawi was to learn about the language and the culture. As my husband and I were learning the language, we started to develop a course based on our learning experience.” As part of tNyasa Ltd, she and her husband developed a Chichewa course together with Paul, their Chichewa teacher. So when the AI4D Africa Language Challenge was launched on Zindi at the end of 2019, Taylor and her colleagues were excited to make a submission.
3RD QUARTER 2020
When AI researcher and language lover Dr Amelia Taylor first moved to Malawi, she soon began learning Chichewa, Malawi’s indigenous official language. She found that there were few resources for teaching Chichewa that covered pronunciation and grammar, or made use of sound and video.
Meet the startups that Airbus
PICKED FOR ITS
#Africa4Future 2020 cohort
3RD QUARTER 2020
Global aerospace accelerator Airbus Bizlab in May welcomed 10 African startups into its three-month long #Africa4Future 2020 cohort.
#AFRICA4FUTURE IS a joint-accelerator programme launched by Airbus BizLab and “Make-IT in Africa,” an initiative developed by GIZ, the German agency for international cooperation. It is implemented with the help of CCHub, a Nigerian start-up consultancy. In addition, UP42, a developer platform and marketplace for geospatial data and analytics, recently signed on as the programme’s technology sponsor. Since 2017, #Africa4Future has accelerated 14 start-ups in Africa. The 10 startups in the 2020 cohort, who were selected from an applicant pool of 212 startups from 28 countries, hail from Ghana, Morocco, Nigeria, Kenya, Rwanda, South Africa and Tanzania. Now in its third season, #Africa4Future’s focus is on remote sensing for precision agriculture and infrastructure development. In applying for the cohort, startups were asked to come up with solutions on how remote sensing for precision agriculture could help respond to food shortages, as well as how satellite technology can ensure the sustainable development of infrastructure across Africa. These are key questions in line with SDG 2 and SDG 9 of the UN Sustainable Development Goals. The 10 startups that were accepted into the programme include among them AI and Data Science firms, they are: AgriEdge (Moroccan): Developing a precision agriculture services platform to improve the profitability of small-holder farmers. Agrorite (Nigeria): Creating a funding and advisory services platform designed specifically for farmers.
Crop2Cash (Nigeria): Working on a platform to connect small-holder farmers to banks, giving access to credit products and ensuring oversight for banks. DMM.HeHe (Rwanda): Developing an end-to-end logistics solution to connect farmers to customers. Epinec (Nigeria): This IT services startup is working on a project management tool to give farmers real-time visibility. Fastagger (Kenya) Developing an AI-as-a-service platform to provide image annotation services to AI-driven businesses. Flamingoo Foods (Kenya): Rice trading startup creating a tool to predict food shortages and food surplus in the East Africa region. GrowForMe (Ghana): Working on a platform to connect small-holder farmers to investors and individuals to grow a specific crop. RuralFarmers Hub (Nigeria): Developing a tool to provide farmers with agricultural best practices and tailored advice via SMS, voice calling or in person. XY Analytics (South Africa) Working on a herd management tool to enable the monitoring of health, movement, reproductive status and location of livestock. Between May and June, the cohort was given access to technical and commercial workshops—as well as mentorship opportunities with Airbus, Deutsche Gesellschaft für Internationale Zusammenarbeit German (GIZ), and CCHub experts and coaches—to push their ideas to the next level. On 11 June, the cohort presented their work to the #Africa4Future executive committee during a virtual showcase. ai
Zindi is building AI in Africa
16,000+ data scientists male 26% female
25 - 34
18 -24 -2 24
28% 2 8% 76% users in 45 African countries
$175,000+ awarded in 60 0 competitions 40Â awesome ambassadors in 20 countries 140,000+ pageviews per week ek 5,000+ Twitter followers
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1 MILLION WOMEN in RPA by 2025
For Tholang Mathopa, the founder of RPA Nuggets — a Johannesburg-based Intelligent Automation, AI and analytical consultancy — AI systems are only as good as the data that is fed into them.
“THEREFORE THE inclusion of women, and disenfranchised / under-represented groups, particularly in AI and Data Science fields can help mitigate this risk,” she says. To that end, Mathopa has embarked on an ambitious mission to include more women in AI, and particularly in the field of Robotic Process Automation (RPA). Her goal is to up-skill and train at least one million women in Africa in Intelligent Automation and RPA in the next five years. Synapse caught up with the visionary entrepreneur for a Q&A that covered her career, the challenges of running an RPA startup as a woman in South Africa, and the details of how she intends to go about reaching the goal of the 1 million women in RPA initiative. Here’s what she had to say.
Tell us about your company in a nutshell
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RPA Nuggets is an Intelligent Automation, AI and analytics consultancy. We help businesses automate operations processes through custom intelligent automation solutions powered by AI and analytics to drive business value. RPA Nuggets was launched in March 2019 and is run by two full-time employees, myself and another female director. The rest of our development team consists of 15 freelance consultants. Our main clients are corporate organisations like banks, auditing firms, insurance companies and any structured organisation with set traditional business processes.
Can you walk us through your professional background and what inspired you to start this business?
I started my career in 2013 as a data analyst for a telecommunications company, just after completing my BSC Computer Systems at Heriot Watt University. This was my first job, I was excited and amped up to learn and grow professionally. Off work, I consumed myself in Microsoft Business Intelligence (BI) YouTube videos and soon certified with an MS BI accreditation. Opportunities flooded in, and I was up for the challenge, which motivated my move to a small insurance firm as a BI developer and later junior enterprise architect. My career advanced to an associate role at a Big Four consultancy where I was called into their analytics team, and was soon asked to become a part of the pioneering RPA team. While I was an RPA developer during the day, I became an online freelance RPA trainer at night, training tech aspirants across the globe for two hours on this new and emerging technology. My role as an RPA trainer was where I exercised my creativity, as at the time, there weren’t a lot of RPA learning or reading material. I did everything from training and curriculum development, to corporate advisory and strategic RPA consulting. I loved it, and loved RPA more! This catapulted my career to joining a New York RPA startup I was freelancing with as an RPA consultant. This saw me travel across the US, UK and Asia, corporate training and consulting. I owe my broad understanding of Enterprise RPA to this experience. RPA Nuggets came into fruition when I realised that South Africa had a staggering 10,4 million unemployed people, mainly youth. I wanted to use my skills to help alleviate unemployment and contribute towards South Africa’s’ preparedness for the Future of Work. I therefore developed a skills development programme that used RPA to help increase trainee’s competitiveness in a market demanding cuttingedge tech skills. It was here that RPA Nuggets, the consultancy, emerged.
How did you initially fund the firm?
Through personal finance and other voluntary services.
How has the company been performing since it launched ? Since inception, we’ve recorded progressive milestones from primarily corporate training with our major market in India. We’ve had an average of 70-100 trainees per month online. Yes, there were some stalls caused by the ongoing pandemic, however, we’ve ceased it as an opportunity to reach out to more women on the vision 2025. RPA Nuggets has launched in Nigeria this year, our biggest B2B2C market thus far.
What can we expect from RPA Nuggets in the next year or two ?
Tech with a purpose!! This is our DNA at RPA Nuggets. We are definitely looking into growing within our continent, using business and technology to tackle African social challenges, especially women inclusion in emerging technology. We are looking into up skilling at least 500 000 African women in 2021/2022, and help advance their careers in Intelligent Automation and other emerging technologies We know our challenges as Africans and we want to resolve them. Technology is a great resource and enabler to effect this change.
Tell us more about the 1 million women in RPA initiative
The 1Million Women in RPA Initiative is a virtual skills development program aimed at up-skilling African women in Robotics Process Automation to increase the representation and leadership of African women in RPA and Intelligent Automation. Our target is 1M women by 2025.
To achieve this, we are currently liaising with trainers across the continent through a train-the-trainer programme, to bring RPA in remote areas across Africa, and ensure women from diverse backgrounds have a chance of participation in the programme. Ultimately, our goal is to have a rich skills development programme that will engage a diverse audience in their own language. Africa is rich in culture and different languages, and we want to use this to our advantage to make the content as relatable and understandable as possible. We are currently working with our trainers to translate our curriculum to fit the language needs from each region, to ensure maximum impact and understanding, as for many English is not a primary medium of communication. Our current partners are Pan African Chamber of Commerce and Girls in STEM Trust. Those who wish to get involved can send their inquiries to email@example.com with subject “2025 1Million Women in RPA Initiative”.
What advice would you give to other women looking to enter this field or start their own companies?
Be pliable, it’s the only way to survive an agile digital world. This means be comfortable with being a learner, a constant learner. To women looking to start their own businesses – Do not allow resistance to discourage you to follow your dreams. ai
Gosh, it’s exciting and extremely challenging. I find myself having to constantly “prove myself” beyond my competence and aptitude. Barriers to funding, market access and strategic networks to advance businesses play at a different scale for women. South Africa can do a better job in prioritising women led organisations for economic development and inclusion by ensuring that women have easier access to resources required to scale and grow sustainable businesses. There’s absolutely no sense in requiring a minimum R1-million annual turnover from a business in the remote Eastern Cape region in order for that business to access funding. What would you say have been the biggest challenges you’ve faced running the startup since launch? Market entry. To a large extent, most stakeholders are holding on to legacy systems and outdated ways of doing business, creating a barrier for new business. Funding – many new South African businesses hail from rural areas and townships. We have fantastic ideas and implement them with what we have, where we are. Easier access to funding opportunities, accelerator programs, bank credit can change the game for South African entrepreneurs.
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What’s been your experience of running an RPA startup in South Africa, as a woman?
The PC is back and 2020 will be its year It turns out the PC’s death has been exaggerated. PC sales grew between 1.1% and 1.5% in the last few quarters of the year, according to Gartner.
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By Chris Buchanan, Client Solutions Director, Dell Technologies
WHILE THOSE don’t sound like massive leaps, they represent a large market that has been declining for several years. Windows 10 is credited for this surge, especially as Windows 7 is leading towards its end of life (EOL). But I don’t think that is the entire picture. Windows 10 upgrades have been taking place for several years, and the market has also gotten savvier about managing EOL. Other factors are driving the adoption of PCs. A specific one is how much closer the PC now sits to smartphones. I recently watched some youngsters work with laptops that had touchscreens. They hardly ever touched the keyboard, instead tapping and swiping on the screen. Yet they were still working on a laptop, not a smartphone. Certain things are much easier to do on a PC than a phone, and users are realising this. They aren’t relinquishing the convenience of their smartphones, but applications are now available on PCs and often easier to use. Convertible or 2-in-1 machines have closed the gap between the two device types. This is in contrast to tablets. If you observe how people sit with tablets, it’s the opposite of smartphones or laptops. With the latter, we sit forward, attentive and focused. But tablets often prompt people to recline. It’s just a casual observation, yet I believe that PCs and smartphones have much more overlap with each other than pure tablet devices. Additionally, the convertible laptop has become the new tablet. Why does this bode well for PCs in 2020? The 2-in-1 machines break down the barriers between the utility of a PC and collaborative culture of a smartphone. You can now flip a laptop into tent mode and use it as an interactive presentation screen on a boardroom table, or cradle it like a clipboard you jot on with a digital pen. In the next year, we’ll see more of the market responding to this trend. Premium 2-in-1 devices
have a stable and growing audience of users who are now going into their second, third and even fourth generations of devices. Mid-range and entry-level laptops are also starting to adopt touchscreens and flip displays. These 2-in-1 devices are also pushing innovation, such as the emergence of dual-screen systems. Dell revealed two such concept devices at CES this year: Project Duet, a dual screen laptop, and Project Ori (for origami), a more compact approach to foldable devices. We also unveiled Project UFO, a prototype Alienware device that puts triple-A PC gaming into a handheld device. All of these reflect the desire for touchenabled devices that are portable without sacrificing performance or excellence. They definitely point us to the future. Convertible devices are not a new form factor. I can recall the first flip-over touchscreen designs appearing 15 years ago. Back then they were exotic and the standard laptop ruled the roost. But today, the habits and expectations of users are driving a change decisively towards convertible devices. Desktop PCs are meanwhile becoming more specialised, yet also more widely appreciated for their versatility. Specialist non-Windows PCs, such as those used by designers, are being replaced by Windows PCs, often for lower costs. Integrated discrete graphics chips and other advancements add a lot of value to modern desktops. The smartphone overlap also appears here: many people use services such as WhatsApp Web on their PCs, and Dell customers use the Dell Mobile Connect app to show their smartphone screen on their PC display. There is a new synergy between the PC and smartphone, created by users who find the two complement each other. Not everyone has realised this yet, but in 2020 that will be the resounding message. The PC is back and 2020 will be its year. ai
Educating Tomorrow’s RPA Leaders Together
What is Blue Prism’s Academia Program?
BLUE PRISM IN THE CLASSROOM
PROFESSOR TRAINING & CERTIFICATION
• Blue Prism training licenses for professors and students • Offer hands-on RPA learning • Attract and retain top student and professor talent
• Blue Prism developer certification for teachers • Curriculum building assistance • “Train the Trainers” for curriculum successtalent
JOB SKILLS FOR STUDENTS
INVESTMENT IN THE RPA INDUSTRY
• Hands-on learning with leading RPA software • On-demand developer certification prep • Proctored certification exams
• Fostering education for tomorrow’s RPA leaders • Building relationships with RPA educators • Building business skills needed today
“The partnerships that grow from this program will seed the next generation of innovators, disruptors and digital business leaders” – JOHN HINDLE, MANAGING PARTNER AT KNOWLEDGE CAPITAL PARTNERS
BLUE PRISM ACADEMIA PROGR AM
For Universities Attract top student and professor talent! Universities can offer cutting-edge technology course curriculums with hands-on Blue Prism connected-RPA training. Blue Prism’s Academic Alliance Managers will work with interested universities to introduce the program, share the required process and technical documents, and guide the implementation of the course into the university curriculum. *Academic institutions offering full time curriculums in technology are eligible for program acceptance.
For Professors Teach real job skills with hands-on learning in the classroom! Professors can use up-to-date versions of Blue Prism’s market-leading connected-RPA software to teach automation developing skills and to design entire curriculums around developer certification. We ensure each professor is properly trained, certified and equipped to successfully lead the future of RPA developers. *Professors must be certified Blue Prism developers to teach Blue Prism connected-RPA course curriculums—on-demand, in-person, and partner-led training and certification opportunities provided.
For Students Learn valuable job skill in the classroom! Learning RPA with hands-on access to Blue Prism’s market-leading connected-RPA platform makes preparing for a successful future in the technology industry easier than ever. With instructor-led classroom training and access to a host of online resources, students can become Blue Prism certified while they earn their degree. *Students who are interested in learning Blue Prism but do not attend an Academia Program Member University can use Blue Prism’s Learning Edition to achieve the same experience, training and certification opportunities.
About Blue Prism Blue Prism’s connected-RPA is an intelligent RPA platform that was designed to be business-led and technologycontrolled. With user-friendly design and easy access to AI capabilities, Blue Prism’s connected-RPA enables operational experts to build innovative process automations while meeting the strictest security and compliance standards. Visit www.blueprism.com.
© 2020 Blue Prism Limited. “Blue Prism”, ”Thoughtonomy”, the “Blue Prism” logo and Prism device are either trademarks or registered trademarks of Blue Prism Limited and its affiliates. All Rights Reserved.
RE-SKILL FOR THE FUTURE of work that’s happening now There’s another big problem that you’ll see occurring right across the front-to-back offices of your organisation; people performing soul-destroying navigation between functions, systems and processes as ‘human middleware’. This is the silent killer of performance, responsibility and effectiveness. You’ll also see people performing activities ill-suited to their innate abilities too - those that are highly stressful, where slow performance or errors are harmful and costly, or activities that require high levels of concentration and repeatability that are almost impossible to perform consistently well, securely and compliantly.
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A better way of working
Intelligent automation that runs a smart, digital workforce that’s ready to be easily trained and put to work by people – while freeing them too – is a better way to manage process-driven activities. We mean people freed to employ their innate skills to manage higher value, more strategic activities. We’re talking about analysing and interpreting data that digital workers can’t understand, making critical judgements, applying this business intelligence to continually optimise or reinvent processes – meaning your people are spending more time with customers, improving their experiences, thinking, problem solving, innovating. Just like the robotics revolution in manufacturing in the 20th century, the same intelligent automation revolution is occurring across white-collar jobs. It will change every aspect of the way work is performed across the enterprise - and it’s all good news. Intelligent automation is being used by the world’s largest organisations that are generating hundreds of thousands of truly transformative use cases. We’re not only talking about generating hundreds of millions of savings and huge operational efficiencies, but people improving business performance, delivering more strategic value generating roles, saving and re-utilising vast amounts of time. We’re seeing people with the capability to transform service delivery and quality, faster expansion of new services, effortless coping with COVID-19 lock-down - even via remote working, and most of all – speed and scalability.
knowledge workers fear losing their job to automation in the next 3 years
New working skills
Our global survey also reveals a need for re-skilling and training, with over three quarters surveyed indicating that data analysis and data science are skills which they are constantly sourcing. We’ll see more value placed on re-skilling programmes and digital literacy education across wider society. Robust measures must be taken to develop talent from within, or your businesses will continue to struggle to attract the best staff. You’ll need to action this fast, as according to the World Economic Forum, retraining people in intelligent automation technologies, developing new human-machine roles and restructuring related work processes, may require three months per staff member over the next four years.
How 123 RPA GO, develops intelligent automation skills for free
We’re playing our part in helping you and your people prepare for the future of work and learn exciting skills that will bring a key differentiator to career paths and professional experience. Our platform is designed for professionals to automate processes with a no-code approach. We offer different e-learning paths from beginner to advanced, with our free course that explains how to automate processes in 3 simple steps.
Automation anxiety – the reality
However, there remains an increasingly outmoded view about automation equalling jobs losses. This whole debate is wrongly informed by the idea that there’s a finite set of tasks and, once these things have gone, there’s nothing left for people to do. In fact, automation expands the economy, expands the number of things that are out there to do. While some jobs could fall to automation, especially those that never suited people, WEF predict that 133 million new jobs could be created as a direct result of the same Industry 4.0 innovations – a global net gain of 58 million. In fact, our global survey indicates that only 33%
Learn more here: https://www.blueprism.com/customers/ develop-your-rpa-skills-for-free/ Blue Prism will be exhibiting at AI Expo Africa 2020, visit their booth to learn more about their solutions. ai
SYNTHESIS ‘TAPS’ INTO the future of payments
pandemic has accelerated the adoption of contactless payments due to the safe interaction when paying since the card does not leave the cardholder’s hand. Mastercard has reported a significant rise in adoption of contactless payments since the start of COVID-19 and this trend will continue as more people enjoy the speed and convenience of contactless. Halo will also boost financial inclusion for small businesses and micro-merchants. “Just think about the benefit to informal traders who could not previously accept debit or credit cards simply because they didn’t have POS terminals. Now they can easily and securely accept payments that are verified online in real-time,” says Aurel. Being able to process card payments using only a mobile App will liberate the appropriate merchants from point-of-sale (POS) devices as well as removing the requirement for installing fixed telephone/data lines before they can start trading. Synthesis has developed the Halo software kernel that has been Certified according to EMV Level 2 standards for both Mastercard and VISA. Halo has achieved the same certification as traditional POS terminals and is more secure than other QR based payment methods. The technology may be embedded in other payment applications from 3rd party developers by making use of the Halo Software Development Kit. It is compatible for any NFCenabled device running Android 7 and above. Synthesis is proud to pioneer a new era for payments as contactless becomes the preferred payment option for customers and merchants. For more information on the innovative work Synthesis has done for its blue-chip clients, contact: Kim Furman, Marketing Manager, 072 236 3572. Synthesis will also be exhibiting its work at AI Expo Africa 2020, visit their booth at the expo to learn more about their solutions. ai
SYNTHESIS, an innovative software development and consulting company has launched ‘Halo’, becoming the first official Tap on Phone technology provider in Africa. In collaboration with Nedbank, the Tap on Phone solution was unveiled on the 30th of June. Halo is a radical advancement in mobile payments that enables secure contactless card payment acceptance on any Android device. The technology is termed ‘Tap on Phone’ due to the way in which a payment card is tapped on a mobile device or phone. It is used by a business or a merchant to ‘receive’ a payment. “Think of ‘Tap on Phone’ as a substitute for traditional POS terminals just without the extra hardware only a mobile device is required,” says Pierre Aurel, Product Manager at Synthesis. This payment innovation should not be confused with mobile wallets (like Samsung, Google, Garmin or Apple Pay) that have been around for a few years. These wallets make use of Host Card Emulation (HCE) where the phone essentially acts as a contactless card and is used by a customer to ‘make’ a payment. In fact Halo is the inverse technology of a mobile wallet – putting simplicity into the hands of small and medium business owners to accept a card payment. Aurel adds that, “We see Tap on Phone playing a significant role in the future of mobile payments due to its speed, convenience and enhanced security. The technology has immense potential for small and micro merchants as it will allow them to accept card payments and enter the digital payment ecosystem without incurring any upfront costs for expensive POS terminals. Additionally, this technology reduces the reliance on cash and reduces any physical contact during the payment process.” The technology arrives at a time where hygiene and reduced physical contact are paramount to society. The COVID-19
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Synthesis launches Halo – the secure, instant, contactless payment solution set to enable all businesses.
Israeli Companies leading the AI industry
• Assisting companies with knowledge, connections and outreach in the SA and Israel markets • Performing technology scouting researches and facilitating B2B sessions between Israeli and SA companies • Participating with national booths and business delegations at Trade shows, conferences and exhibitions • Accompanying and supporting the individual exporter in the marketing activity abroad. • Initiating and applying international trade agreements and maintaining existing agreements. • Raising investments and strategic cooperation Between Israeli and SA companies Over the last 10 years, Israel has positioned itself as one of the leading ecosystems for Artificial Intelligence start-ups. The top companies, which are pushing the boundaries in the AI industry, are: - Lemonade was founded in 2015 by Israeli entrepreneurs Daniel Schreiber and Shai Wininger, combines behavioural economics, and artificial intelligence. Lemonade uses AI and chat bots to deliver renters and homeowner’s insurance policies in over two dozen states across US. Healthy. io was founded in 2013 by Yonatan Adiri. The Israeli medical tech start-up that developed a platform to turn smartphones into sophisticated diagnostics devices capable of analysing urine samples. Healthy.io has two FDA clearances for a Smartphonebased urine albumin test, called Dip.io that aids the diagnosis of chronic kidney disease, developed a consumer-focused UTI testing service in partnership with UK pharmacies, and recently unveiled a new digital solution in the US for the management of chronic wounds. Razor Labs is a Tel Aviv-based start-up founded in 2016 that builds tailor-made neural networks and helps mining and manufacturing companies “reap the benefits arising out of the AI revolution. “The start-up’s Data Mind platform virtualises manufacturing processes and its Visual Mind video analytics platform uses several AI applications for corporate objectives. The company also runs an eight-week educational program focused on deep learning engineering, from which it hires candidates, and builds tailored executive shorter sessions based on I.T. Razor Labs is bootstrapped and profitable and has offices in Perth, Australia and Tel Aviv. SentinelOne was founded in 2013, the Israeli cyber security firm that developed an AI-based platform to secure endpoints including laptops, PCS, servers, cloud servers, and IoT devices. Its system analyses data in real-time to identify anomalies and provide a response to attacks. SentinelOne has offices in Mountain View, California and a development centre in Israel. ClimaCell is a US-based AI-powered weather intelligence platform company created by Israeli founders. ClimaCell automates operational decisions and action plans based on how historic, real-time, and future weather will affect
businesses. It produces hyper-local weather forecasts using vast quantities of traditional and non-traditional data (IoT devices, drones, cellular signals, sat com signals, and street cameras) and targets weather-sensitive industries. I Know First, Ltd. is a financial technology company that provides daily investment forecasts based on an advanced, self-learning algorithm. The underlying technology of the algorithm based itself on Artificial Intelligence. It also based itself on machine learning and incorporating elements of artificial neural networks and genetic algorithms. Israel AI – Accelerators, Research Programs, and Capital Venture Investments The AI for Good 2020 accelerator program helps purposedriven ventures in Israel advance their AI solutions to create positive social transformation. The program reflects shared belief that the biggest opportunity for AI is not for AI to shape our future, but for people to shape AI to make the future we want to see. The program seeks to nurture transformative change through AI. There are many research programs in the AI industry in Israel. AI2 is bringing people closer to information, by creating and using advanced language-centred AI. As a scientific approach, they believe in combining strong linguistics-oriented foundations, state-of-the-art machine learning, and top-notch engineering, with a user-oriented design. Tel Aviv University are working on smart artificial intelligence programs. Scientists and researchers are working on several artificial intelligence and machine learning projects. AI involves developing machines that can perform tasks that are characteristic of human Intelligence. Team8 Capital, is a new venture capital fund that will focus on technology investments in data, artificial intelligence (AI) and cyber security.Team8 Capital will invest at the seed and other early rounds of funding, expanding on its model that builds new companies from scratch. Tel Aviv-based market research firm IVC Research Center published its summary report on Israeli tech and venture capital in 2018. Local tech companies raised a record $6.4 billion across 623 deals, 17% more than in 2017, according to the report. The fourth quarter of 2018, the year’s strongest, saw a total of $1.82 billion in investments in Israelilinked companies. The number of newly founded Israeli start-ups that employ Artificial Intelligence has risen over the years and so has the capital they have raised. Israel is home to over 1,000 companies, academic research centres, and multinational research and development centres specialising in Artificial Intelligence. The start-up nation of Israel is targeting today’s hottest tech sector by deploying its expertise in cutting-edge data analysis, software and hardware engineering talent, and proven entrepreneurial skills. The Israel trade mission looks forward to connecting and building strong relationships between South Africa and Israel in the AI Industry and other sectors. ai
The Trade Mission’s objectives are:
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The Israel Trade Mission to SA is an official Israeli government agency, part of the Israeli Ministry of Economy that is based in Johannesburg, South Africa.
SOUTH AFRICAN ACADEMIC
elected chairperson of UNESCO Ad Hoc Expert Group on Artificial Intelligence
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Professor Emma Ruttkamp-Bloem, an academic at the University of Pretoria’s Department of Philosophy, has been elected as the chairperson of the United Nations Educational Scientific and Cultural Organisation (UNESCO) Ad Hoc Expert Group (AHEG) on Artificial Intelligence (AI).
THE UNIVERSITY of Pretoria said in a statement on its website in June that the group will formulate a recommendation for the first global standard-setting instrument on the ethics of AI following the decision of UNESCO’s General Conference at its 40th session in November 2019. The AHEG comprises of 24 renowned specialists with multidisciplinary and pluralistic expertise on the ethics of artificial intelligence. The group, which has been appointed by UNESCO for a 24-month period, began work in March. The group is made up of four members each from six regions namely: Western Europe and North America, Eastern Europe, Latin America and the Caribbean, Asia and the Pacific, the Arab States, and Africa. The four representatives in the Africa group are from South Africa, Ghana, Rwanda and Cameroon. Professor Ruttkamp-Bloem is also a member of UNESCO’s World Commission on the Ethics of Scientific Knowledge and Technology (COMEST) and the AU High Level Panel on Emerging Technologies. Her work focuses on, among other things, developing AI for the growth and benefit of humanity. She explained in the statement that the reason why there hasn’t been a global instrument for the ehtics of AI yet is not so much because of the fact that it is unchartered territory, but more around the nature of AI as a disruptive technology. “The complexity of its impact on the core sectors such as civil society, the future of work, security and surveillance, the financial sector, and education, and the difference in AI readiness of countries across the globe, that have contributed to the difficulty around formulating a global instrument,” she said. The absence of a global standard where AI is concerned, she added, doesn’t necessarily imply that there aren’t efforts across the world to research AI and how it can be used to benefit humanity. There has been an explosion of work on the ethics of AI, she pointed out. These efforts include the work of the Council of Europe’s Ad Hoc Committee on AI (CAHAI); the work of the European Commission’s High-Level Expert Group on AI, including the Ethical Guidelines for Trustworthy AI; the work of the OECD Expert Group on AI (AIGO), the OECD’s Recommendation of the Council on AI; the G20 AI Principles, and many others. There are also many documents related to the ethics of AI developed by the private sector, and professional organisations such as the IEEE’s Global Initiative on Ethics of Autonomous and Intelligent Systems and its work on Ethically Aligned Design; the World Economic Forum’s Global Technology Governance:
A Multi-stakeholder Approach; the Montreal Declaration for a Responsible Development of AI, and many more. While Professor Emma Ruttkamp-Bloem is not yet at liberty to say specifically what issues the AHEG is considering, she cautioned that the general issues facing the development of AI are complex and include real threats varying from the transgression of the right to privacy to security threats posed by the possible deployment of lethal autonomous weapon systems. Other threats relate to concerns around bias, transparency and accountability in the context of automated decision-making systems. “Fairness usually refers to structural bias present in data, which is sometimes inadvertently, and sometimes advertently, exacerbated by machine learning processes. Think here of gender or race or ethnic or age-related bias as examples. Transparency refers to making evident the processes of the system and links closely to issues of explain-ability. One – very simplified – way to think about it is that transparency relates to understanding how machine learning systems are designed, developed and deployed, while explain-ability relates to understanding the outcomes of these systems. Accountability relates to ascribing ultimate human responsibility for the outcomes produced by machine learning systems, and the auditability and traceability of the workings of such systems, as well as the consideration of ethical questions such as for instance, should there be blanket disclaimers allowed in this kind of technology. As mentioned already, a lot is being done on a wide array of platforms to mitigate these threats and challenges,” she said. She added that her vision for the group is that it will contribute to a global instrument that will ensure that humans remain at the centre of interactions with AI technologies – while she stressed that humans should take up this opportunity with integrity and responsibility and not just take it for granted. “The challenge is to become the best humans we can be very fast. Above all, AI technologies should enhance human flourishing and peace and harmony and protect human rights. I see the most important objective of the work of the Bureau as continuously striving to find the most efficient ways in which to include and reflect the expertise and contribution of every member of the AHEG throughout this process we have embarked on, in order to ensure the content of the Recommendation is as rich and balanced as possible,” she added. ai
to New Frontiers Talking robots. Self-driving cars. Medical systems trained to find signs of tumours. Every day I get to work with many of the world’s elite AI developers while collaborating with our own teams of researchers to prototype what, at one time, was viewed as science fiction. By Alison Lowndes, rtiﬁcia nte i ence e EMEA, NVIDIA
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At NVIDIA, I’m also able to devote time to continuing my sustainable development work in Kenya, Brazil, and elsewhere, sharing knowledge and enabling communities to improve their lives using technology. Especially through my work in Kenya I have a strong network of experts across many fields who all help together “harambee” at the community level. I look forward to future projects fusing this with my day job, making healthcare more accessible and sophisticated, autonomous drones for environmental management, ferrying supplies to hard to reach areas and online learning opportunities through the Deep Learning Institute. Some of the most profound work I’m proud to be a part of is with the Frontier Development Laboratory (FDL), a research accelerator that brings solutions to some of the global society’s most existential threats. Simultaneously, FDL is equalising both gender and racial inequality. We consistently have 30-50% female participation (the worldwide tech community only manages 10-15%) and our teams comprise nationalities from around the world. This year, we’ve continued our work, from home.
If you’d like to learn more about using AI, please contact me: firstname.lastname@example.org Download the NVIDIA Company Brochure Alison Lowndes will give a talk titled “Fuelling the Artificial Intelligence Revolution with Gaming” at AI Expo Africa 2020. ai
FIVE YEARS ago I joined NVIDIA after studying artificial intelligence at the University of Leeds. Since then I’ve had the honour of being part of many fascinating projects, including work with NASA and the European Space Agency, with the United Nations on a “digital ecosystem for the planet” and other AI4Good initiatives, and on AI software able to predict extreme weather and help with climate change models. NVIDIA fosters an innovative culture. It’s a place where people pursue their life’s work and aim to make a difference in the community. Now more than 16,000 people strong with the recent acquisition of Mellanox, the company is supercharging computing while also reducing the carbon footprint of data centres around the world. NVIDIA graphics processing units (GPUs) are used all over the globe, by scientists, designers, artists, and gamers. We innovate at the intersection of virtual reality, high performance computing, and AI — at the bleeding edge of visual computing. NVIDIA technology is fuelling the AI revolution in areas like simulation, virtual robotics, and off-world navigation on the surface of the Moon and Mars. NVIDIA RTX technology enables photorealistic, high-definition visuals within virtual worlds, for everything from gaming to training virtual AI agents. Our latest NVIDIA A100 GPU, based on the NVIDIA Ampere architecture, is up to 20x more powerful than its predecessor. It achieves these incredible speedups through full-stack invention — from the chip and systems to the algorithms and applications they run. NVIDIA GPUs are in every major cloud compute provider and accelerate eight out of the 10 most advanced supercomputers on the planet. Our own supercomputer, NVIDIA Selene, is the seventh fastest in the world and capable of 4.6 exaflops of parallel computation (aggregate peak fp16 for all clusters). That’s one quintillion (1018) floating point operations per second. Our open-source software and communities drive progress and accelerate computing further in a variety of domains, such as AI at the edge with NVIDIA Jetson, healthcare with NVIDIA Clara, and data science with open-source RAPIDS and Apache Spark 3.0.
STELLENBOSCH UNIVERSITY LAUNCHES
African Data Science Academy
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Stellenbosch University (SU) in June announced the launch of its Africa Data Science Adacemy.
SU ESTABLISHED and launched its School for Data Science and Computational Thinking last July with the vision to be a world-class institution for data science and computational thinking in and for Africa. The university said in a statement in June that the school has been hard at work to facilitate nonconventional, trans-faculty approaches to teaching and research in data science and computational thinking at the university in an interdisciplinary way. The school has now established the African Data Science Academy (ADSA) to carry out the school’s mission to facilitate human capacity building in data science and computational thinking at the University, nationally in South Africa, across Africa and globally. It develops and presents open courses offered by the school as well as bespoke courses developed for our industry and academic partners. According to Prof Kanshukan Rajaratnam, Director: School for Data Science and Computational Thinking, they are inviting academia and industry to partner with the African Data Science Academy for their training needs and would like to impact both researchers and professionals who want to build their skills in Data Science related fields. “The African Data Science Academy is a way for the School for Data Science and Computational Thinking to build capacity in this area not just in South Africa and Africa, but across the world. It is an exciting moment where we can bring our world-class academics and internationally known Stellenbosch University quality to the rest of the world. ADSA does not just offer another online course, but adds value through interactions and with our presenters, and delegates have the opportunity find out how to apply the principles in their own fields.”
This coming July, ADSA will be offering two accredited online short courses in partnership with the African Doctoral Academy at SU. Both courses will take place online from 20 to 24 July 2020. The first course is an Introduction to Statistics with R. R, which is a statistical software programme particularly powerful in data analysis and graphical representation. This course offers an introduction in the application of the programming language R to statistical analysis. The second course is an Introduction to Data Science. The short course is designed as an introductory overview to data science explained at the hand of the data science project life cycle. Prof Rajaratnam says that they have designed the short courses with “high-touch activities in mind,” such as reviews, quizzes, assignments and group work, as well as live or virtual and Q&A sessions with the course presenters. “The courses are taught by Stellenbosch University’s own world-class lecturers from the Department of Statistics and Actuarial Science (Introduction to Statistics with R) and from the Department of Industrial Engineering (Introduction to Data Science). The fact that we are offering these courses online allows for students in any part of the world to take these courses and allows us to take Stellenbosch University’s world expert academics to the rest of the world.” Further information on the courses can be found on the School for Data Science and Computational Thinking website here, http://www.sun.ac.za/english/data-scienceand-computational-thinking. Potential students can also contact dataschool@sun. ac.za. ai
Leveraging digital technologies to deliver enhanced data insights with Microsoft
Digital transformation provides organisations with countless opportunities to affect change and embrace advances in cloud, data, and artificial intelligence (AI). But for many, it is difficult to extract the required insights from the sheer amount of data at their disposal.
Knowledge mining can be defined as the ability to retrieve information and extract insights within a vast amount of data. For example, Azure Search enables this by using built-in AI capabilities to uncover latent insights from all the content of an organisation across its documents, images, and media. These AI capabilities empower businesses across industry sectors to discover patterns and relationships in their content, understand sentiment, and extract key phrases to name but a few. As a practice, knowledge mining gives companies the ability to consume and process all types of content across multiple locations and formats. They can extract new insights and knowledge from the content by using deeply integrated and prebuilt AI technologies across vision, speech, and language. In turn, this knowledge can surface through a variety of tools such as search, data visualisation, and business applications to make it available to customers or employees. Companies who are willing to embrace digital transformation see a clear need to automate the understanding of data from their unstructured information. Many are already automating the extraction of data from their unstructured information. In turn, this will be used for analytics, making it searchable, and visualised in a dashboard. The ability to transform information into a comprehensible structure can expand visibility into real-world business practices, streamline cumbersome processes, and create new knowledge and actionable insights. A case in point of how knowledge mining can deliver value can be seen with a Microsoft implementation at Archive360, an intelligent information independent software vendor. By incorporating Microsoft Azure Cognitive Search, the organisation lets customers ask complex questions of petabyte-sized datasets quickly and cost-effectively. For companies in highly regulated industries like financial services, healthcare, pharmaceuticals, and insurance, this alleviates a significant concern when it comes to data regulation.
Archive360 used Azure Cognitive Search to deliver stronger data containerisation, machine learning (ML) capabilities, and robust Azure Cognitive search tools to its customers. This has enabled customers to perform faster, smarter, and more flexible searches through their archives than ever before. And by integrating the Azure Cognitive Search Azure Cosmos DB, customers can now also easily identify the connections between people and data. The technologies also enable elastic scaling in both directions. This means customers can scale out, charge back the business unit for that scale out, and once results are produced scale back in.
Tying data together with Azure Synapse Analytics
To truly unlock the potential of data, an organisation must be able to effectively integrate it across all touch points. And this is the field in which Azure Synapse Analytics plays to its strengths. Revealed by Microsoft at its Ignite conference in November last year, Synapse is a cloud data warehouse platform with integrated data lake functionality. It aggregates, integrates, and facilitates an array of Azure data services that has operated as islands of functionality. This limitless analytics service is the glue that brings together enterprise data warehousing and big data analytics. It gives companies the freedom to query data on their terms, using either serverless or provisioned resources and does so at scale. Synapse combines these environments with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence (BI) and ML needs. Synapse is therefore able to deliver insights from all organisational data irrespective of where it is stored. Data professionals can query both relational and non-relational data at petabyte-scale using the familiar SQL language. For mission-critical workloads, they can easily optimise the performance of all queries with intelligent workload management, workload isolation, and limitless concurrency. It is deeply integrated with Power BI and Azure ML to greatly expand discovery of insights from all company data and apply ML models to all intelligent apps. Continued on page 90
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Getting to grips with knowledge minin
For example, not being able to provide specific data with audit and accountability information on request can result in significant financial fines.
DATA IS a messy business. Not only does it span media types and databases, it is continuously growing and evolving. And within its confines lies valuable knowledge that must still be converted to make sense for anyone trying to use it. This is where knowledge mining becomes invaluable.
Africa’s AI Initiative Cirrus is a private sector led initiative bringing together academia and industry for the establishment of a world class AI research and application capability, to enable a transformation in scientific research and commercialisation. Targets
#1 in Africa
Powered by renewable energy.
✓ Most powerful computer system in Africa by a factor > 5 ✓ Top 50 globally
~ 2000 m² ~ 3 MW
✓ ~ 3 megawatts of solar to support operations. ✓ > 10 MWh of storage
2000 square meters (21 528 square feet) to house Cirrus operations, excluding the HPC centre. Data Management Platform for all the AI datasets supporting: ✓ “FAIR” ✓ Open Access ✓ Data Commons
FABRIC edge node to support next generation internet research.
Data from tens of millions of dollars of scientific instrumentation.
> 35 Universities Participation from at least 3 national laboratories.
Including the African Research Universities Alliance (ARUA).
> 13 Countries
~ 35 million USD Core engineering capability: ✓ ✓ ✓ ✓
Hardware Software Data Machine Learning
~ 650 m²
650 square meters (7000 square feet) stateof-the-art HPC centre.
Academic programs: ✓ ✓ ✓ ✓
Residency Intern Postdoc Assistantship
Target FOUNDRY Fund capitalisation.
Opening Africa to AI Copyright Cirrus AI (Pty) Ltd
Cryo-EM structure of COVID-19
Analysing nanomedicines for cancer immunotherapy
Railway track faults
Underpinning innovation in most scientific disciplines.
Vehicle dynamics simulator
Track carbon emissions from power plants
Financial reckoning with AI
Nuclear waste remediation
Data centre cooling and industrial control
Predicting disease progression and selecting therapy
Extreme weather patterns from highres climate simulations
Predicting lung cancer
Exascale deep learning to accelerate cancer research
Tackling climate change with machine learning
The future of agriculture
Robotics and AI to improve crops and harvests
AI interactive graphics
Using machine learning for code recommendation
A deep learning approach to data compression
Cut drilling costs
Accelerates efforts to develop fusion energy
Accelerating advanced energy materials Discovery
Predict the useful life of batteries
Analysing lithiumion battery electrode damage
6G Autonomous wireless systems
Next-Generation Context-Aware wireless networks
Application of AI to mobile network operation
How AI will shape the network of the future
Quantum chemistry: AI to tackle Schrรถdinger equation
Deep learning in the study of materials degradation
The search for the perfect material
Space group of a structure from the atomic pair distribution
Deep learning and density functional theory
Generative models for fast simulation
Uncovering hidden scientific knowledge
Analyse images from very little data
Deep learning technique for Navier-Stokes
Precise measurement of quantum observables
Logistics: Stochastic optimization problems
Lawyer-Bots are shaking up jobs
Measuring patent claim breadth
Computing genes to support living clean
AlphaFold: Protein folding
Deep learning for real-time gravitational wave discovery
3D seismic fault segmentation
Simulations in structural biology
GUIDED BY AI: How Renewable Africa 365 is applying AI in the rural electrification of Nigeria by Daniel Mpala
NIGERIA HAS crippling power challenge. Despite having installed electricity generation capacity north of 13 000 megawatts, only half of that is available with reports that Nigerians receive less than 4 000 megawatts a day. According to Bloomberg article published in late May, only 60% of Nigerian citizens have access to electricity. 2018 World Bank statistics reveal that while 81.7% of the country’s urban population has electricity, only 31% of its rural population has access to power. With an estimated population of about 200 million people, this means roughly 120 million people, most of them in rural Nigeria, live with no access to electricity. That’s the problem that Ademola Eric Adewumi and Omachonu Joshua Dominic are trying to solve through Renewable Africa 365 (RA365). The NGO, which they established in 2019, works with local governments in the country to install off-grid mini solar power substations.
The duo were faced with a problem – given the vast size of a country like Nigeria, how does one find the most suitable spots for solar installations across the West African country’s communities? Last November Renewable Africa 365 partnered on this challenge with Omdena – a global innovation platform for building AI solutions to real-world problems through collaboration – with the intention of coming up with a way to identify the most suitable locations for the NGO’s renewable energy micro-grids. Over the course of two months, Omdena mobilised a global team of 40 data scientists and machine-learning engineers to come up with a solution that is among the first real-world machine learning solutions to be deployed in Nigeria. The Omdena team developed a tool that helps to survey and validate locations before the installation of the solar panels which power Renewable Africa 365’s off-grid sub-stations. The solution combines satellite imagery and population data to create an interactive map that lists the top Nigerian regions with high demand for electricity where the installation of solar panels would not only be highly feasible, but would also have the most impact on the community. Speaking during an Omdena Demo Day webinar in July which showcased the project, Adewumi said the Omdena team has “changed our lives”, with the tool having identified about a 1000 potential locations across Nigeria, “In order to get the job done, it’s not about providing the solutions (off-grid sub-stations) to these people. We want to make sure that the solution gets to the right people at the right places and Omdena has really helped us to achieve that,” added Adewumi.
So, how did they do it?
‘Confidence to confront individuals who matter’
Left to right: TransWatt engineer,Ademola Eric Adewumi and Omachonu Joshua Dominic
Adewumi says the NGO’s micro-grid prototype will generate 2000W over a 24-hour run-time once fullycharged. An Internet of Things (IoT) system will remotely control the micro-grid and portable solar devices from an admin panel that will track, monitor and recommend optimal usage with smart controllers and GX monitoring devices. Check out this video on RA365’s prototype here. RA365 is working on with German off-grid and mobile power supply firm TransWatt on a Solar Home Scheme (SHS) which intends to roll-out to communities identified by Omdena’s model. The SHS consists of a portable solar device that powers two light bulbs, one laptop, two mobile phones and one TV set Inspired by RA365’s collaboration with Omdena, Adewumi said the NGO is looking to extend its research and development arm to come up with homegrown research on the country’s energy problems and to figure out the best ways to solve them with what is readily available. “We want to make more head way in improving the IoT in our micro-grid systems, impacting thousands of Nigerians, and lifting them out of energy poverty,” said Adewumi. ai
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Prior to its collaboration with Omdena, Adewumi points out that RA365’s problem statement was “loosely defined”. The NGO now focuses on providing power to off-grid communities which are 15km away from the grid. “We also determined that millions of people in Nigeria have never had contact with electricity in their lives. So we now adjusted our lenses to focus on these rural areas,” said Adewumi. The data and insights generated from the Omdena project, he added, has given the NGO the confidence to confront “individuals who matter”. “There are several discussions going on right now which would not be possible otherwise. It also gave us insight into energy poverty and a lot of companies have also been talking to us as a result of the outcome. Solar energy is capital intensive so it takes time to actually have a solution on the ground, but we make steady progress every week,” he said. At the time of writing, RA365 was in talks with the Lagos State government, which the NGO says has welcomed the initiative.
Simon Mackenzie — lead machine learning engineer at Omdena — speaking at the same webinar, explained that the project team’s first objective was to locate communities where installation of the solar panels would add more value. “That meant looking for people who lived in a fairly close area that didn’t have electricity, or lived more than 15km from the grid,” he explained. Ideal locations include those that are closer to public amenities like clinics, water points or schools as well as ones that comprise buildings that aren’t too far spread out from each other (as this would save money on cabling). The team also needed to find locations where the population was concentrated. The challenge there was there was no reliable ground data to go on. As a workaround, the team had to use satellite imagery and public data sets — including one from a polio vaccination scheme which was backed by surveys — to build a population model. The Omdena team also had to contend with insufficient data on which areas actually had a working power grid. Oddly enough, as Mackenzie explained in the webinar, power companies in Nigeria don’t know where their grids are. Using a combination of satellite imagery, machine learning and manual checking, the team managed to locate electricity infrastructure like power lines and used this data to identify areas with functional power grids. Using cluster analysis, the Omdena team identified communities of about 4 000 people who lived within a small radius and did not have access to a nearby electricity grid. Mackenzie said the team then came up with an interactive map which identifies target communities or settlements where solar panels will add most value. Using machine learning models powered by data like solar efficiency and proximity to public amenities, the tool provides priority list of target locations. “As you gain a better understanding of costs and financing, and other things you can re-sort that list and change your priority,” he explained. The data on the list is, he added, is available at a detailed level across the entire country. Mackenzie explains the project in detail in this Omdena blogpost, also check out this blog for a more technical take on the project.
W W W. A S H A N T I . A I
WE ARE ASHANTI AI
AND WE BELIEVE IN DOING THINGS
A LITTLE DIFFERENTLY.
Ashanti AI uses artificial intelligence to empower companies in the Supply Chain to make decisions faster, improve efficiency and increase profits. Our team of data scientists use an assortment of skills and viewpoint, together with a toolbox of techniques to drive value your way.
DIAGNOSTIC DESCRIPTIVE ANALYTICS
NATURAL LANGUAGE PROCESSING
We are here to design new solutions to existing problems you might experience, as well as the newly discovered ones. We do this through our three AI cloud based products: Predictive Maintenance, Warehouse Labour Management and Vernacular Sentiment Analysis.
OUR PURPOSE IS TO USE AI AND DATA SCIENCE TO: Increase PROFITS
Discover POTENTIAL Make better decisions FASTER
Improve operational EFFICIENCIES
F O R YOU R P EO P LE, BY O U R PEOPLE
Create clear defined rules
Predict Future Scenarios
OUR CLOUD-BASED PRODUCTS
Communicate and better understand data
â€“ Powerful insights powered by Ashanti AI
Ashanti AI uses artificial intelligence to empower companies in the Supply Chain to make decisions faster, improve efficiency and increase profits.
PREDICTIVE MAINTENANCE Millions of rands are lost when trucks, heavy loaders and mining equipment fail unexpectedly. If only you could timeously predict when and why your machines break down. Predictive Maintenance is a tool that combines the power of IoT and predictive analytics to assist asset owners in predicting when a particular machine will fail. This helps reduce unplanned maintenance costs.
WAREHOUSE LABOUR MANAGEMENT What if cleverly processed data could help work out exactly how much manpower you need every day in your warehouse? With our Intelligent Warehouse Management product, we analyse your business processes to determine when and what labour you need for your warehouse. With allocation of warehouse labour, you can fulfil orders on time and curb unnecessary cost. We also assist you with increasing labour productivity and accurately incentivising labour through gamification.
VERNACULAR SENTIMENT ANALYSIS Ever wondered what people are saying about your company? Understanding the emotional subtleties of regional or geographic vernacular is almost impossible when pulled from mass amounts of online social comments. We use Multi-lingual Social Media Intelligence to find out what the general sentiment about your company is on social media. Our systems are fluent in South Africa. We can zone in on specific demographics to determine how you can better serve your diverse customer base.
email@example.com +27 (0) 11 712 1300 www.ashanti.ai
4th Floor | The Mall Offices 11 Cradock Avenue | Rosebank 2196 Johannesburg | Gauteng | South Africa
to Better the World I had, what was for me, the oddest experience a few months ago. While filling up our family car with petrol, my two boys, who are aged 7 and 6 respectively, were looking at the Warning Stickers next to the petrol pump. As kids are want to do, they were telling me what was allowed and what was not allowed, “No matches! ...No phones!” then, following a pause, “What’s that third one, dad?”
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By Thomas Fowlers, CEO, DotModus
“OH. THAT’S the no-smoking sign. You can’t smoke here...” I remarked. Surprisingly, to me at least, he replied, “What’s Smoking?”. And so, the next few minutes were spent explaining to a 7 and 6-year-old what smoking was. I found this astounding because, on the whole, children these days can consume more content than ever before. They can consume content entirely on-demand and sheer amount of content available means they tailor their choices at will. So how was it, that with everything that they watch online, neither of them had yet encountered smoking? I found this astounding. You see, in our household, there were a few obvious candidates responsible for their sheltered view of the world:
1 - Neither my wife, I nor their grandparents, aunts, uncles and cousins in our family are smokers. So my boys have never seen someone smoke before. 2 - Broadly speaking, smoking has been missing from popular culture in mainstream media - certainly neither Iron Man nor Captain America smoke. Continued on page 78
All the tools and expertise you need to automate and digitalise your business. Enjoy the unmatched eďŹƒciency of a cloud-powered, automated business today.
Using ML to Better the World
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Continued from page 76
3 - My boys consume all their on-demand media through the YouTube Kids app. This media is automatically screened and filtered by Google’s Video AI platforms, where content not applicable for children is filtered out or removed entirely. It was this last reason that got me thinking about the use of ML and AI in our everyday lives in such a way that makes a positive difference. The amount of content that content makers consistently upload to platforms like YouTube is astounding - 720,000 Hours of video are uploaded to YouTube every day. That’s over 500 hours uploaded EVERY MINUTE! It is impossible for human beings to filter through and moderate content at this scale. For these platforms to be viable for children, organisations like Google must put machines at work to assist in the effort to find, categorise and filter content that is unsafe for children such that platforms like YouTube Kids are safe enough that I can happily leave my boys to consume the content they want, on-demand. In Q1 of 2019, YouTube removed 8.3 million videos. Of these, 76% were found by machine learning classifiers and over 70% of these were removed before they had any views. It was this level of automated content processing that contributed to the fact that, for nearly 8 years, my two young boys had never seen a video of someone smoking. (A note here for parents: This ML capability employed by YouTube does not, of course, negate our responsibility as parents to understand what their children are consuming - you should always be aware of what your kids are up to online. But it does go a long way to making our jobs as parents not just easier, but even remotely possible based on the sheer volume of what is available on YouTube.) The dangers in the user-supplied content model are obvious: The sheer amount of content, and the potential ability for those that seek to harm to supply this content, means that the world of content consumption for adults and children alike is fraught with danger. For example, we live in a world where bad actors can use technologies such as DeepFakes to seek to influence in a way that is nigh impossible for human beings to detect. The only cure for DeepFakes is Machine Learning processing categorisation. We need the help of AI-driven machines, working non-stop 24x7, to help us
keep the content our loved ones consume, safe. It is only through the process of AI-driven automated content processing, categorisation and filtering that we can even begin to safely use platforms like YouTube and others. So what does this all mean for organisations? Google has, over at least the last 5 or more years, shown their dedication to making ML and AI available to everyday organisations to automate their workloads. From the open-sourcing of Tensorflow to the release of CloudML, Google has made the tools available to bring ML, AI and Automation into your organisation in a mature, scalable and reliable fashion. Do you want to process and categorise video like YouTube? Use the Cloud Video Intelligence API from Google Cloud Platform (GCP). What about training, hosting and managing custom models built in Tensorflow? Google has custom hardware (Cloud TPUs) and the AI platform to process your models at scale. Want to process text or voice? Google has pre-trained models for Speech-to-text and NLP that are proven to be best in class. The point is this: organisations like Google and YouTube have been solving problems using ML and AI for nearly a decade. We can stand on the shoulders of giants and use these technologies to not just improve the way we do business but improve the lives of our customer bases as well. How will you use ML and AI to improve your business and, perhaps, even make the world a better and safer place? DotModus is a Google Premier Partner with over 100 certified Data Scientists and Data Engineers. If you’re interested in understanding how Google’s technology can change your business, speak to us. DotModus will be exhibiting at AI Expo Africa 2020, check out their booth to learn more about their services. ai
We have deployed the solution in: 1. The formal retail space where the system is being used to identify sales and stock levels by sku for a dozen Brand owners using daily sales and “stock in store” levels generated through the till points. a. The intelligence in the platform is assimilating the
data and creating sales assumptions by store by region, advising on optimal stock holding levels, adjusting the detail based on macro influences such as major events, weather pattern shifts, etc.. b. One of the key opportunities that is in current development is the use of the data to drive dynamic resource allocation based on changing sales and stock patterns in store, identifying out of stocks or predicting sales higher than current stock holding and auto instructing merchandisers to fulfil. 2. The Distribution to wholesaler and distributor leg of supply chain is a massive part of the African Route to Market for most Brand Owners, our Cognizance platform is allowing the players in this space to have all their data in a single repository and mined to understand the friction points as well as opportunity for category growth. a.Having the live feedback on distribution costs based on the change in wholesaler buying patterns allows for a very quick adjustment to distribution strategy. b.Understanding what product sells in what region and store based on the surrounding community allows for better allocation of capital investment. At a point the Data Lake will become the nerve centre of business using AI to drive appropriate growth strategies and resource allocation to ensure best category growth across all supply chain channels in both manufacturing and FMCG. ai
THE SOFTWARE modules all add value at some point in the chain but there are very few vendors that supply a software platform that would allow for a single version of the truth of movement of a single product from manufacture right up to purchase in a retail environment, so the emphasis then shifts to the concept of consolidating the data into a single data repository where the transactions generated by each step in the chain is recorded for analysis and response. Data repositories are not a new phenomenon and have long been used to power BI tools to deliver insights and levels of trend analysis and forecast, but having spent the last 18 years in building a software business that provides line of sight in the supply chain industry (Macmobile) it became very apparent to the team that insights on their own are not enough to encourage growth, a more granular view of friction points with a “Deviation to immediate remedy” mindset was needed to stimulate growth in any of the supply chain and manufacturing sectors. Cognizance was born because of the shift in mindset, a Data Lake with sophisticated data processing capability to produce “calls to action” as the deviation occurs!
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In the space that is the “Supply Chain” the friction points that are created by the plethora of different software modules used at different points add to a drain on the profitability of companies, from the ERP, to the Warehousing Management system, Logistics and Distribution, receipt at the Distributor and into retail space and then as importantly the movement or lack thereof of that product onto the consumer.
CONVERSATIONAL AI Is Transforming
Financial Services Financial service institutions across the globe are constantly searching for innovative ways to meet their customers’ ever-evolving needs. FinChatBot is currently working with some of South Africa’s top financial service providers to build and implement tailored conversational AI solutions to improve customer experience and drive business results.
3RD QUARTER 2020
By Antoine Paillusseau, Co-founder and CEO, in hat ot
HERE ARE three important functions conversational AI can perform to improve customer experience and keep your call centre agents focusing on more complex customer needs.
which invariably leads to enhanced user experience and over all satisfaction levels.
Acquiring New Customers
Payment and debt collection is always a sensitive subject. Customers often feel uncomfortable when dealing with live agents regarding outstanding payments. Many corporations have begun to leverage the power of automated agents to facilitate the debt management and collection process, leading to a situation that benefits both company and customer. Conversational AI provides an interactive and more discreet way of engaging with customers about payments and debt, while also offering several options to make payment or payment arrangements if required, thereby empowering the customer to make decisions. Companies can (and should) also equip their automated agent to display a level of empathy, as this would enhance a customer’s level of comfort in dealing with the bot. Being able to understand and respond to a customer’s particular situation leads to a happier customer and, ultimately, a loyal customer. It is no secret that conversational AI will become a major factor in transforming the financial services industry going forward. The benefits of conversational AI are just too great to ignore. At FinChatBot, our conversational AI solutions are developed to accomplish all of the goals outlined above and more. Our passion for technology ensures that we remain on the cutting edge of development. The tone, language, and approach is fully customisable to meet the ethos of our clients’ brands. Our software constantly learns and assimilates information to provide a personalised experience for each customer across a variety of different communication channels such as WhatsApp. The goal is to meet customers where they’re at, with a platform that they’re comfortable with.
Imagine an automated agent that greets customers with a friendly “hello!” every time, knows all the right questions to ask, can advise on the full range of products and services available, and works 24/7! A dream scenario for any company, right? The reality is that conversational AI can perform all of these functions. It can be used to generate leads for businesses by engaging with visitors to the company website or mobile app, answering basic questions about products and services that the company offers and, even provide customers with the opportunity to finalise the sale on the spot. Engaging with automated agents means that customers wouldn’t need to wait until the business doors opened on Monday morning; they could conclude the deal at any time of the day or night. Conversational AI is great for streamlining the acquisition and sales process, as it can answer the straightforward questions that customers may have while providing the opportunity to connect with a live agent when needed.
Serving the Needs of Existing Customers
This is the area in which conversational AI can prove to be most valuable. Customers today expect to receive instant responses to their queries, as well as 24-hour availability, from the financial institutions that they deal with. While a live human agent may not always be on hand to provide this type of support, automated agents can be tailored to meet both of these expectations. They allow customers to engage at any time and place to deal with any common queries or complaints, or even submit claims. Conversational AI solutions can be personalised with multilanguage capabilities, tone and flow optimisation and more to provide intelligent and human-like conversation with customers,
Collecting the Debt
FinChatBot will be exhibiting at AI Expo Africa 2020, check out their booth for more information on their conversational AI solutions ai
TECHNOLOGY MATTERS, but Should it Follow or Lead?
It has become common knowledge that the businesses of tomorrow are the ones that transition from “things and people” to “technology and networks”. This is evident in the recent proliferation of the adjective “Digital” in most C-Suite titles and businesses either being “born-in-the-cloud” or traditional businesses undergoing some form of digital transformation. By Ugan Maistry, tech ALTHOUGH “GOING digital” seems to be the common phrase, there is no consensus on what this actually means. To some executives, it is the deployment of technology in their current business (business process optimisation). To others it is about a whole new way of engaging with customers (digital customer experience) and to others it is about an entirely new way of conducting business (exponential digital business mindset). One would presume that the varied definitions is a function of their individual business circumstances (competition, cost pressures, customer expectations, industry disruptions, regulations, etc.). Whilst none of the definitions are incorrect, every digital transformation journey needs to be guided by strategy, a business model that supports that strategy, enablers that are needed to execute the business model and the orchestration of enablers to reach your destination.
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Digital Transformation in our new “normal”
When Joseph Schumpeter argued that when something new is created, it brings about the demise of something old; his reference point was human ingenuity and innovation. Today, we are experiencing existential threats in the form of climate change, biological pandemics, geo-political wars, terrorism (including bioterrorism and cyberterrorism), and famine. Our response to COVID-19 and the subsequent precautionary measures (including our risk adjusted lockdown) has been a catalyst for change – change in the way we live, learn and work. We adopted online learning, work from home via online collaboration tools and mass adoption of online retailing. When the dust has settled, would we or should we go back to how we used to live, learn and work? As society, we will soon realise the benefits of essential travel (and reduced carbon emissions), cost savings from reduced office space rentals, peer learning (via online platforms), improved employee productivity (coupled with output based remuneration models) and the value of quality time with our loved ones. In this moment of creative destruction, should we not be assessing the way we configure our businesses for customer centricity, uninterrupted supply chains and maximum efficiency? Should we not be redefining our digital transformation strategies and priorities to align with our new “normal”?
Perhaps it should be evolution and not revolution
Yesteryear, most executives took a blue-sky thinking approach in redefining the purpose of the organisation and its digital business strategy. Whilst this may seem revolutionary and necessary at the time, it does not lend itself to the agility required in the post pandemic world, where social distancing measures and onerous safety requirements affect your access to markets and the efficiency of your supply chain. In our new normal, as organisations resume their activities, the imperative will be to reinforce trust among their employees around creating a safe and healthy work environment. Can it be the previous buffet spread in the canteen during lunch breaks or endless in-person meetings? More than likely, we would have to settle for pre-packed sandwiches from the vending machine and more virtual meetings. What does this mean for productivity, balance and sense of purpose? Are you going to achieve pre-pandemic productivity levels with these restrictions in place, given that by definition we are social creatures? In the new normal, perhaps the quick wins should be around how we ensure business continuity by automating activities and tasks, whilst respecting social distancing restrictions. In the back office, this will certainly create a contactless file and document transfer. Perhaps these types of interventions have not taken place to date due to the nature of the process (e.g. multiple decision point inputs) or it being cost prohibitive to integrate the process. Notwithstanding, any business continuity plan is going to be dependent on having optimised (preferably digitalised) business processes. This will surely remove all friction in the system, ensuring that customers and suppliers can engage with the enterprise in an efficient, timely and cost-effective manner in our new normal. So perhaps evolution may be a more measured response after all.
Robotic Process Automation (RPA) tools offer potential ways to automate repetitive, manual, rules-based tasks. Whilst RPA is not the answer to all automation conundrums within the enterprise, it does offer a compelling alternative to traditional BPM tools. Instead of months-to-years to automate business processes within the enterprise, RPA can
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Technology Matters... achieve similar results in weeks-to-months, creating a team of “virtual workers” that operate 24X7, executing error-free, repeatable business processes. Apart from the use case of reducing manual interventions in repeatable business processes, one can use the technology to reduce headcount in batch driven data input / output processes, link to legacy or external systems (in a nonintrusive manner) that would otherwise be too cost prohibitive to integrate into your internal business process or avoid major systems reengineering for the purpose of integrating or automating part of a business process. Thus, if there is a requirement to have a speedy, cost effective, error-free, repeatable automation of business processes, then RPA should be a consideration. Perhaps it is time you lead and let the technology follow.
strategy is core to the success and sustainability of your organisation, but how do you execute that strategy in a technological environment that is volatile, uncertain, complex and ambiguous (VUCA)? The reality is that to leverage the opportunities and avoid the pitfalls of this industrial revolution requires specialist knowledge and learned experiences. FIRtech has a unique blend of expertise based on decades of experience and through our experienced team of management and technology consultants and our network of partner software vendors we help you shape and implement facets of your digitalisation strategy including artificial intelligence (AI), cyber-physical systems (CPS) and enterprise digitalisation Contact: E: firstname.lastname@example.org M: +27 73 335 0997 W: www.firtech.co.za
FIRtech will be exhibiting at AI Expo Africa 2020, visit their booth to learn more about their RPA solutions. ai
In today’s global world of business, an effective digital
MACHINE LEARNING in Health in Africa
Lately when I wake up ,and look at the world around me I recognise so many negative words and how it’s impossible for us to achieve basic human rights and access to things like healthcare for people who need it the most and can’t afford this very basic service.
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By John Kamara, o n er f are o
OUR POLITICIANS, administrators and custodians of finance are worried about processes than they are about caring about people who are dying every day. Then, I think about how a data-driven ecosystem with the patient at the center ,and very basic machine learning tools that have no interest in self-serving interest can help us to create a seamless flow of data that makes it possible to provide better healthcare and use machine intelligence to solve problems that would have taken us years and thousands of deaths to solve. So the question I ask myself is very simple -- what is more important? How can AI help us solve problems or how would it require us to provide better education for people who have to retrain so that they can also become more valuable to the system? While developing our health platform Afayrekod I pondered about the real problem we were solving. The more I thought about it the more a simple solution became extremely complex ,and I realised why it has been a difficult for years. Simply put self-serving interest and policy have made it impossible. I wrote a simple model on movement of data with the
patient at the center of the data flow, AI driven diagnoses, and other chart notes on paper as the start of our journey into solving the data problem in healthcare. I always knew this was an area in which technology could help improve healthcare, and hoped it would also improve patient care. For example the possibility of going to different hospitals that are not connected and knowing that each one has access to your health data and can use that historically information as the baseline before treating you is a value that patient-centric health solutions provide. It also allows us to use accurate and consistent data to provide better insight for patients and help doctors treat patients much better and faster as well. Since then, we have advanced our product and found a number of innovators who are on the same path, advancing their products to make it possible for the patient to access their health record, and health service anywhere and anytime with an AI engine at the back to model multiple problems that are now becoming solvable. Also, advancements in electronical medical records have been remarkable, but the information they provide
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from a Pan-African perspective. Africa can leapfrog Europe and America in the use of machine learning, free flow of data and ownership of data driven by the patients to create a world class healthcare ecosystem with the limited resources we have at the moment. The challenges are there, and people ask me every day about the possibility, but the truth and reality is simple -- nothing life changing happens without hard work ,and overcoming negative and myopic self-serving agendas. The value of machine learning in healthcare is its ability to process huge datasets beyond the scope of human capability, and then reliably convert analysis of that data into clinical insights that aid physicians in planning and providing care, ultimately leading to better outcomes, lower costs of care, and increased patient satisfaction. Still, machine learning lends itself to some processes better than others. Algorithms can provide immediate benefit to disciplines with processes that are reproducible or standardised. Areas like radiology, cardiology, and pathology can benefit the most from machine learning in healthcare I believe that Africa has the opportunity to embrace machine learning, and free flow of accurate patient centric data in the health space to deliver world class treatment and healthcare to our population. We can also teach the rest of the world something new and a better way to manage healthcare. At Afyarekod our mission is to create a seamless flow of patient data via our platform -- with the patient at the centre of the flow the data -- and to allow healthcare facilities access to that data and as well as the ability to store the data they generate accurately. We then use AI to help doctors and health facilities model diseases and also treat patients efficiently. ai
is not much better than the old stagnant data in silos. If technology is to improve care in the future, then the electronic information provided to doctors needs to be enhanced by the power of analytics for accurate and free flowing data, as well as through machine learning focused on symptoms and deep learning. Using these types of advanced analytics, we can provide better information to doctors at the point of patient care. Having easy access to vital information and other key signs when doctors see patient is routine and expected in this day and age. Imagine how much more useful it would be if a doctor was shown a patients risk of cancer based on accurate and free flowing data or stoke, coronary artery disease, and kidney failure based on the historical blood pressure readings, lab test results, race, gender, family history and other relevant data. We need to visualise data as the first point of access into using machine learning and how information to health practitioners can help us reduce the burden on the few health facilities and health resources we have. Machine learning in healthcare will also allow doctors and other health practitioners to generate more revenue and equalise the power of data between the health facility and the patient allowing for a more proactive healthcare ecosystem. The use of advancements in data sciences and machine intelligence can help us make better decisions about patient diagnoses and treatment options, while understanding the possible outcomes. Patients can also self-manage their health (Healthcare happens outside the hospital and treatment happens inside the hospital). This is the problem we are trying to solve at Afyarekod,
CHALLENGES OF THERMAL Cameras - by Healthvision
When the global pandemic was declared, Healthvision realised it needed to help businesses empower the safe return of their workforce during and after COVID-19 in the smartest, simplest and most accurate way possible.
WE ACTED swiftly, pivoting the business, which previously focused on the retail sector, to accommodate secure and seamless management of many thermal facial recognition cameras across multiple locations, on one platform, in the cloud or on-premise. Within ten days, we had successfully adapted the Healthvision platform to provide corporations with a solution they could roll out immediately and remotely. During implementation, we encountered two significant challenges, and this is how we overcame them.
1: Economic challenges lead to budget constraints
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Despite our clients’ huge desire to implement the solution, Healthvision’s biggest challenge were the initial hardware costs. The initial capital investment for terminals was R35k, and we have since managed to reduce this to R29k. We implemented a manageable monthly pay-per-use license fee and reduced our margin on the hardware to only cover the necessary costs; modification, insurance, transport and installation. Thus in passing on any price decreases to our clients, we offer them the best value; the lowest possible cost on a high-quality product. Further to this, we simplified our pricing model into three components: • A size dependant platform fee. • A per-fee per scan, decreasing with scale. • An optional COVID-19 health questionnaire/declaration form fee.
2: Privacy and Facial Recognition Algorithms
The controversies around facial recognition are quite wellknown and recently came into the spotlight again with the airing of John Oliver’s show Last Week Tonight with John Oliver (episode 15, John Oliver explores the impact of facial recognition software on the world). It is also well-known that initial facial recognition algorithms were trained on limited, and often biased, datasets. This led to facial recognition algorithms not working on all races and genders equally. Healthvision worked to overcome this difficulty by ensuring our facial recognition algorithms do not work on faces, but instead irises. In addition, we have worked with users to ensure their faces are recognised, both with and without masks. We believe that facial recognition software should work equally as well, no matter who is having their temperature checked.
A Way Forward to Ethical Facial Recognition Healthvision believes we lead the way in ethical facial recognition camera usage because of our unique algorithms, and we strive to partner clients whose usage plan meets our principles. Our vision is to become a leader in ethical facial recognition and to use artificial intelligence for good. We’re purpose-driven to deliver seamlessly integrated health technology for you because your staffs’ health is a representation of your company’s health. Get in touch with us on email@example.com or for more information, visit heatvisionai.com ai
AI, for good. Healthvision is a simple, automated, electronic screening software platform . Weâ€™re purpose-driven to deliver seamlessly integrated health technology for you because your staff health is a representation of your company health. Weâ€™ll help you monitor your workforce, customer, member or patrons health effortlessly. We do this through seamless management of many thermal cameras across multiple locations, on one platform, in the cloud or on-pemise. And a bonus, we can do it all remotely and so can you. Contact us for a consultation, email firstname.lastname@example.org
Doubles Investment for African Start-Ups
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Lagos-based venture capital (VC) fund Ingressive Capital announced in June that it has doubled its investment vehicle to back high-growth, tech-enabled startups across Africa to $10-million.
INGRESSIVE CAPITAL invests in the startups in subSaharan Africa, particularly in four markets, namely Nigeria, Ghana, Kenya and South Africa. The fund’s portfolio includes Paystack, Tizeti, Jetstream, 54gene, OZÉ, and Bamboo. The investment fund aims to support the next generation of African innovators. The VC fund targets pre-seed and seed-stage tech-enabled businesses in the B2B space that provide tech solutions to Africa’s traditional billion-dollar industries, as well as B2C fintech and internet companies. Ingressive Capital invests between $200 000 to $400 000 and targets 10-per cent ownership into companies it funds. Up to 20-per cent of its limited partners – investors in its fund – run some of Africa’s largest traditional businesses. This gives the portfolio access to business development and Pan-African markets. In addition, up to 80-per cent of their limited partners run later stage investment funds. Through Ingressive Capital’s network of limited partners, the VC fund can help companies get follow-on funding from abroad. Some Ingressive Capital’s new investors include the Nigeria Sovereign Investment Authority, Plexo Capital, Platform Capital, Michael Seibel (C.E.O of Y Combinator), Techstars, WTI and over 10 other top funds and accelerators. Seth Levine, Managing Director of Foundry Group;
Kai Bond, Partner of Courtside Ventures; Maurice Werdegar, and President and CEO of WTI make up some of the fund’s advisors. Commenting on investing during the economic times brought about by COVID-19, Ingressive Capital founder Maya Horgan-Famodu pointed out the fact that many billion-dollar companies have been founded or found their footing during economic downturns and market contractions. “We know that creativity blossoms when resources become scarce. We launched and grew Ingressive through Nigeria’s last recession. As far as global businesses, IBM found its market and scaled through the Great Depression. Zendesk launched in 2007 and raised in 2008, and Airbnb was founded out of the 2008 downturn,” said Horgan-Famodu. “WhatsApp, Uber and Venmo launched in the 2009 recession. And on the continent, Safaricom was founded in 1993 from Kenya’s worst economic performance since its independence with inflation reaching 100% that year, and mPesa started in 2007, and grew through the following years’ global recession,” she added. Looking to apply for funding? Email Uwem@ ingressive.co for deals in Nigeria; william@ingressive. co for opportunities in Ghana, or apply at www. ingressivecapital.com for opportunities elsewhere in Africa. ai
Data Science on Demand – Is it a thing? At The Data Shack - we believe it is! Could you call on an experienced Data Science Team, like your trusted GP? Is it becoming A Thing?
Setting up an effective Data Science Practice in Your Business, with the right team of people and objectives from the get-go, can be daunting and expensive. Skills and Experience are scarce, Experience of setting up an effective Competency Centre hard, and appropriate Mentoring and Training, even harder. Whether you: • • • • • •
Are a Small, Medium, or Large Enterprise Need a Full Team as a Service Need Full or Temporary Help to Start Up Need to Embed and Grow a Data Science Practice Need Temporary Team members as a Service Need assistance in Mentoring and Training your winning Data Science Team
Work with our Team of Experienced Data Science Practitioners using Industry best practices The Data-Shack is just the THING!
The Data-Shack | www.data-shack.co-za | email@example.com | 011 881 5604
Leveraging digital technologies to deliver...
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Continued from page 69
Its studio environment provides a unified workspace for data preparation, management, warehousing, big data, and AI tasks. Data engineers can use a code-free visual environment for managing data pipelines. For their part, database administrators can automate query optimisation while data scientists can build proofs of concept in minutes. Business analysts can securely access datasets and use Power BI to build dashboards in minutes all using the same analytics service. Walgreens, a drugstore chain with more than 9 200 stores across the US, Puerto Rico, and US Virgin Islands, services approximately eight million customers daily, creating a wealth of data points. To generate insights that help store managers and staff provide customers with the products they want and best manage inventory, these transactions are compared to at least two years’ historical data across the supply chain. To optimise this environment, Walgreens opted for Synapse as the environment could provide it with the security, operational, and data integration benefits it required. Within three months, Walgreens was able to migrate its entire on-premises data warehouse for inventory management into Synapse. Data flows into the cloud through Azure ExpressRoute and into Azure Blob storage. Users can consume the data through a Web application developed in-house, direct query to the database, or through visualisation tools such as Microsoft Power BI. This has significantly enhanced decision-making at the organisation by letting users quickly visualise and analyse data.
Machine learning for a digital environment
The final component of unlocking the potential of the data an organisation has access to is that of ML. This is a data science technique that allows computers to learn to use existing data, without being explicitly programmed, to forecast future behaviours, outcomes, and trends. The advanced ML capabilities of Azure enable companies to quickly build, train, and deploy ML models. This is done through Azure ML, Azure Databricks, and ONNX (Open Neural Network Exchange). When it comes to the learning component, Microsoft technologies focus on three steps – collecting and preparing data; training and evaluating the model;
and operationalising and managing the process. The Azure ML service provides a cloud-based environment that a business can use to develop, train, test, deploy, manage, and track ML models. ML in action can be seen through the work BP has done to enable its scientists to explore the potential of new energy deposits. Using the Azure ML service, they can build more finely tuned, accurate models in less time to help them better gauge available hydrocarbon services. But this is just one instance. The organisation has established its own AI Centre of Excellence within the company that relies on Microsoft technologies to facilitate several AI and ML goals. It is looking at creating autonomous platforms where employees can more safely manage day-to-day operations remotely using AI. For its part, ML is used to help the business make better decisions about scheduling transport ships to drive greater efficiency and reduce energy consumption. At BP, the cloud-based Azure ML service facilitated the development of models based on historical data and used to predict future outcomes. During feature engineering, scientists analyse existing data and isolate the most important variables that contribute to an accurate prediction of the recovery factor. Algorithm selection determines the logic that will be used to turn those reservoir data variables into a recovery factor forecast. Scientists test multiple algorithms to determine which gives the best performance. And once they have chosen the algorithm, the scientists conduct hyperparameter tuning, which involves adjusting the parameters and feeding the new ones into the algorithm, finely tweaking them to enhance model performance even further. By using the Azure ML service, the organisation has peace of mind with automated ML knowing that it is exhausting all the possible scenarios and using the best model for its inputs. Collating and analysing data do present significant challenges for organisations around the world. But it does not have to be the case. Using readily available Microsoft technologies, companies can capture the true potential of one of the most significant assets they have at hand – their data. Those who do it best, will be the businesses driving more innovations across all spheres of operations in the years to come. For more information on the range of Microsoft technologies or for a demonstration, please contact us or visit our eBooth at AI Expo Africa 2020. ai
Intelligent Customer Service Automation From EmailTree AI & Blue Turtle Technologies
“The end-to-end AI-driven hyperautomation solution to reinvent customer service.” The ever-increasing volume of digital customer communications represent a large organisational cost, and slow response and resolution times have a great impact on the customer experience and advocacy. In today’s economic climate it just isn’t feasible to scale customer service teams with increases in customer bases and service requests. Introducing Em ailT ree A I , the end-to-end AI-driven hyperautomation solution to reinvent customer service…
EmailTree AI, in strategic partnership with Blue Turtle Technologies, offers an intelligent, end-to-end customer service automation solution that leverages natural language processing (NLP), artificial intelligence (AI), sentiment analysis, real-time language detection and translation, and assisted machine learning (ML) to understand, categorise, and route incoming emails, automate tasks, and
intelligently compose a suggested email response for the agent. Furthermore, the level of automation and human supervision can be configured by the organisation based on business rules and AI confidence levels. Thus, over time, the solution will learn and grow in confidence, and can eventually automate the entire service request and resolution process.
EmailTree AI will be showcased at AI Expo Africa, 3-4 September 2020. To see how we can assist you in revolutionising your digital customer service, get in touch. Visit our website, or contact our African Strategic Partner, Blue Turtle Technologies: EMAIL: firstname.lastname@example.org PHONE: +27 (0) 11 206 5600
TRAINING THE NEXT GENERATION
for improved visual intelligence -
Focus on Industry 4.0
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Even before the COVID-19 pandemic hit, headlines in the media were painting a bleak picture of education and training, both locally and globally. According to a recent article by Silvia Montoya, Director of the UNESCO Institute for Statistics (UIS), 617 million children and adolescents worldwide—six out of ten—are not reaching the minimum proficiency levels in reading and mathematics. According to UNESCO data, 91.3% of the total enrolled learners worldwide have been adversely impacted in some way or another during the COVID-19 pandemic. These students will be the workforce of the future.
With the added gaps that have now been exacerbated because of lockdown measures across the globe, we have even more reason for concern, especially in a time where the world is changing faster than you can say industry 4.0.
A fresh look at foundational skills training
Lectorsa is a social impact business in education working to improve outcomes for students in their chosen career choices while helping them to lead more productive and responsible lives. The outcomes of our systems are measurable and impact directly on the way individuals see, work with and remember visual information. EYEBRAINGYM, our latest online system is based on data and results gathered on LAB-on-line (our BETA-system) and
brings together ten years’ of online implementation experience. It combines this knowledge with cutting edge technology geared towards upscaling abilities for the development of the workforce South Africa needs for Industry 4.0. EYEBRAINGYM is designed to help our users to see more, read faster, learn quicker and remember better. The ability to process volumes of information and use new knowledge creatively to address challenges will become more vital within the context of Industry 4.0. Each person will, more than ever, need the abilities to learn, unlearn and re-learn vast amounts of information as quickly and efficiently as possible. Neuroscience confirms that your brain is a self-organising creative system. Every skill and ability you have was constructed in a specific region or regions of your brain, as a result of training and application. Learning is connecting neurons: developing neural pathways and enhancing neural networks.
Adequate reading does not develop naturally. If this is not accurately developed, it becomes a life-long challenge. Using visual information to make intelligent choices becomes an impossibility when we are not functionally literate.
Visual intelligence is the ability to process, understand and express visual information. The basis of visual intelligence is reading with adequate comprehension.
How Eyebraingym makes it possible online
But there is hope. Outcomes achieved with more than 100,000 online user profiles indicates that as our users improve their visual processing in reading, they also increase in the mental energy that they then can devote to understanding complex ideas. It is the integration of foundational areas in reading development and combining various advanced skills and strategies that provide an entry point to multiple literacies and improved visual intelligence. Eyebraingym focuses on improving three measurable factors, gauged against international norms and standards, namely the visual processing factor (VPF) and cognitive development factor (CDF). VPF is measured as words per minutes (wpm) read within the parameters of the readability of the material. CDF is measured as a percentage of comprehension against the complexity of content. The combined VPF and CDF give us the third AIU-factor (action-interpret-understand). The Eyebraingym virtual coach helps each user to overcome challenges in time management, and by using years of research and data ensures best personal outcomes as individualised sessions are built to provide best personal improvement in visual skills, reading, comprehension and cognitive development for each user. Executive function, meta-cognition and mindactivation play a vital role in every course compilation. Eyebraingym is positioned for mass-market uptake and to become one of the solutions needed to redress gaps and challenges in the education and training sectors of the future by using the latest research in neuroscience, reading development and cognitive skills. Join us in the #ReadingRevolution of the future #YesiCan #VisualIntelligence Contact : www.eyebraingym.com, +27828203745 email@example.com firstname.lastname@example.org Lectorsa will be exhibiting the EYEBRAINGYM system at AI Expo Africa 2020. Visit their booth to learn more ai
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Why training visual intelligence is important
The impact of the pandemic exacerbated previous fault lines in the education and training sector, and we are facing a global tsunami of illiteracy. Because illiteracy is one of the leading causes of delinquency, poverty, frustration, and depression in all global communities, we should all sit up and take note. Illiteracy is a major cause of a loss in productivity and a decrease in financial health. It causes a general decline in lifestyles and wellness amongst all communities. The current economic situations across the globe have made this phenomenon even worse.
Neuroplasticity is the brainâ€™s ability to reorganise itself by forming new neural connections throughout life. Connections within the brain are continually becoming stronger or weaker, depending on what we use. This is the â€˜muscle-buildingâ€™ part of the brain, the physical basis why repetition strengthens the power of choices and actions. Over time it becomes automatic. Eyebraingym (and its range of activities) is designed to develop foundational and advanced learning skills through augmenting the science of neural wiring to bridge the gap between information and knowledge by training and optimising neural pathways in the brain of each user. Eyebraingym use actions within the reading process to re-wire the brain to produce healthier and stronger minds.
THE FUTURE OF BREAST Imaging is NOW
South Africa In 1924, Fanny Rosenow, an avid breast cancer activist requested to publish an article in the local New York Times regarding a breast cancer support group. Puzzlingly upon asking, she was put through to the editor of the newspaper.
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By Kathryn Malherbe, CEO, Medical AI Solutions
WHEN HE responded he simply stated: “Well, we can’t really use the word “breast” or “cancer” in our newspaper…. Perhaps you should reconsider calling it a support group of the chest wall?”Needless to say, she hung up. If the fight against breast cancer seems like a never ending series of misguided schemes and false hopes -- much like the ongoing wars we currently face against drugs, terrorism and poverty -- it’s because none of these “enemies” has ever been just one monolithic opponent which can be fought with one type of weapon. Breast cancer remains the highest rate of mortality in South African women, and the current tools and weapons used for its ultimate destruction is lacking. Artificial intelligence and deep machine learning has skyrocketed the medical industry the past few years, estimated as a billion dollar industry by 2025. Computer aided detection is a long withstanding tool used by radiologists for over 30 years in mammographic imaging. The initial attempts however, were limited, as the input was feature-driven and had limited data used for training of an algorithm.Latest AI and DML can attain massive data input for data set training, with retrospective imaging output. The current development in breast cancer imaging the past year, has led to an inert fear of overtaking the role of a specialist physician, however due to a lack of appropriate knowledge in its use, there is a misperception of its major role in augmenting and ultimately improving their diagnostic capabilities. The latest artificial neural networks and support vector machines have been able to receive valuable data input. They are utilised as second reader support for radiologists under much pressure to perform optimally with mass data and thousands of patients annually. Identification, segmentation and prediction of a breast cancer type is limited to histological output by a histopathologist, however Med AI Sol has managed
to develop a patent pending algorithm capable of these features using old adage ultrasound methods in a revolutionary new method of image analysis. Breast cancer is an elusive enemy of the imaging sector, as certain types are prone to subtle changes or “cloak and dagger” appearances, often overlooked or missed during regular screening procedures. The main advantage of implementing AI in such instances, is the ability to pick up false negatives and to aid in the detection of missed cancers. For this both benign and malignant data sets are required for data set training to allow the neural system to have high sensitivity and specificity in its diagnostic prediction. Even more important is appropriate local policy frameworks; much needed for appropriate security measures, cloud hosting and ethical standards related to medical imaging AI software. Numerous international policies exist to this extent, but in the South African context, there is a unique approach to socio-economic and financial challenges. Various questions arise with regards to biomedical ethics and AI: • Who is responsible for AI output, moreover an error in prediction output? • Who gains financial control over AI systems in South Africa? • How would AI promote South African economy in such a way that job creation and youth engagement is encouraged? Medical AI Solutions has managed to implement such measures in a one-of-a-kind software solution. Both physician and patient benefits from its use by means of smart artificial intelligence algorithms to aid detection, but also user friendly patient app for education and support during their treatment journey. The software is a convenient “black box”, mobile and hands free, ideal for rural communities as well as private institutions wanting to improve their diagnostic output.
Invisio AI powered by Clarius Mobile Ultrasound Systems and Nvidia Dotcloud Digital Pty Ltd
The software has linkage to a high resolution hand-held wireless ultrasound probe with the ability to segment, identify and predict breast cancer types on ultrasound.
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A patient associated with the physician using this product, will have free access to a patient educational and support app, which allows information regarding their treatment journey to be explained in a language they understand.
96 Supported by Pink Drive, Breast Health Foundation, We Belong Group, Breast Cancer Support Pretoria NPO
Medical AI Solutions is also promoting youth engagement and education by promoting access to training in AI and technical support programmes, to enhance their understanding and promote job creation in South Africa. Our company is focused on improving the lives of all South Africans, and our passion, drive and need for AI and DML innovation is our key focus to success. Medical AI Solutions will be exhibiting at AI Expo Africa 2020, visit their booth to learn more about their products. Also join Kathryn Malherbe for a talk titled â€œInviso AI - Innovation in breast cancer detectionâ€? ai
A new BioMedical Innovation combining Artiﬁcial Intelligence & Deep Machine Learning
BREAST CANCER REMAINS THE HIGHEST RATE OF MORTALITY IN WOMEN IN SOUTH AFRICA. One of the reasons for this is a lack of appropriate diagnostic infrastructure in both public and private sectors. Our artiﬁcial intelligence software allows an accurate and speedy diagnosis of breast cancer to allow quicker turnaround times to surgical intervention. Our vision is to promote patient-based outcomes in the healthcare industry. Built on world-class Nvidia hardware, MedSol AI’s solution caters for the high speeds of urban connectivity as well as isolated rural environments without internet access, ensuring no one is left behind.
Endorsed by Roxanne Zowitsky LLB (Cum Laude) | Breast Cancer Awareness Activist | Mom of two daughters | Co-director of Breast Cancer Support Pretoria NPO
decisions in an uncertain economy
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COVID-19 has changed many things for businesses: online sales have surged; consumers behave differently; and uncertainty and anxiety has increased.
LOOKING BACK to previous crises, like the 2008 Financial Crisis or the ‘Spanish Flu’ of 1918-20 can be a guide for how things might change with this new crisis. Both of these crises resulted in fundamental changes in the structure and functioning of the economy, accelerating existing trends. For example, the Spanish Flu led to increased use of social security; the Global Financial Crisis accelerated a number of existing technology trends. However, looking back at history does not help business owners and managers with day-to-day decision making. Rather what is needed is tools to help make better decisions. Particularly now, bad decisions can have fatal consequences, and better decisions can separate companies that thrive from the rest. Decision-making under uncertainty is something that humans struggle with, particularly when conditions are in a state of flux like they are now. Humans have a variety of behavioural ‘quirks’ – they are inclined to see patterns when none exist, they overweigh recent events when making decisions, and over-emphasise catastrophic events with low probabilities compared to more likely ones with lower costs. Machine learning approaches, which combine real-time economic data with customer data, can overcome these quirks, helping pick up new behaviours early, and in turn, reduce the uncertainty surrounding business decisions. Predictive Insights is a company taking this approach to help their clients make better decisions. They curate an ever-expanding set of real-time data of what really matters in the economy; things like physical mobility, online behaviour and social media chatter. This data is then combined with a customer’s own data and fed through a machine learning platform, to uncover patterns which humans cannot see. These insights can then be used to create bespoke and accurate short to medium term forecasts which can then be used to optimise operations, and stock, staff and price at the right levels. This approach came into its own during the
COVID-19 crisis. As the economy opened back up after lockdown, trading conditions were very uncertain but many businesses had to make important strategic business decisions - balancing the costs of benefits of reopening for themselves, their staff and customers. Pent-up demand meant that those outlets that did open often traded at higher than usual levels but managers had to make decisions on whether these conditions would continue into the future and how the trading conditions would evolve as the pandemic progressed. Predictive Insights’ real-time data and machine learning models were able to quickly identify new buying patterns during this period of flux, and allow businesses to quickly adjust to these. Machine learning models quickly identified changes in peak trading hours as more people worked from home, but these changes that differed depending on the ‘catchment area’ of the store. These models quickly adjusted as people began to trickle back to offices. They also recognised early changes in the types of products bought, as people pivoted to bigger quantities to avoid frequent trips to stores. This allowed restaurants to become more efficient by defrosting food earlier in the day for new lunchtime rushes and switching staff from evening schedules to earlier shifts. They also helped retailers switch ordering to bigger pack sizes, and to place these products in the distribution centres where they could be shipped to clients quickly. These quick responses resulted in improved efficiency of operations which will continue beyond the crisis. It seems likely that the COVID-19 crisis, like crises before it, will accelerate already existing trends. One of these is augmenting human decision-making with insights derived from real-time data and machine learning. During uncertain times, this can become a company’s competitive advantage. Predictive Insights will be exhibiting at AI Expo Africa 2020, check out their booth to learn more about their solutions ai
SCALING INTELLIGENCE In Software Development
Qualetics is a response to serving the market opportunity resulting from heightened awareness all businesses have for mastering their data to analyse performance, better serve their customers, and improve organisational decision-making. More and more often companies want to be able to say something like “Though our primary business is ____ we also consider ourselves a data company.” Qualetics makes that happen.
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By Sumanth Vakada, o n er an a etic Data Machines, Inc
QUALETICS DATA Machines, Inc. offers a software platform aimed at simplifying the implementation and organisation wide adoption of Data Analytics (DA), Artificial Intelligence (AI) and Machine Learning (ML) capabilities for small, medium and large businesses. The platform allows companies that generate or manage large amounts of Data to implement Data Analytics, AI and ML capabilities with significantly reduced cost, effort of implementation and time compared to traditional methods of similar implementations available in the market. Data Analytics and AI (Machine Learning/Deep Learning) solutions are expensive propositions for most companies. They still come with an R&D tag attached and few companies have operationalised Data Analytics and AI within their systems and products owing to Costs, Resource Demands & Infrastructure Needs. Such complex solutions are out of reach for many businesses and especially Startups and other IT firms that deal with data regularly. This is where Qualetics improves the status quo by offering a solution that simplifies the onboarding of Analytics and AI to companies and reduces the complexity of implementation from taking months and years to weeks if not days. Traditional Analytical solutions cater to either Data
Streaming or Transportation, or Data Visualisations or Advanced Algorithm Building. Such tools can be categorised as DIY Analytics where the onus is on the team looking to use these solutions. Qualetics has developed a solution that integrates the three components above, Data Transfer, Data Visualisations, Data Outcomes with Advanced Analytical models and in a package where integration with client applications is made easy through REST API, a universally adopted mechanism for seamless communications between applications. Technologies such as a custom message broker capable of receiving high throughput data, entirely custom-built visualisation packages and domain specific models set us apart from the current Data Analytics and AI Landscape. Our Data Streaming layer, supports data transmission from software applications as well as IoT enabled devices, broadening the scope of implementation. Qualetics comes with a simple proposition that it enables companies to distinguish themselves as a “Data Company doing X” with our ability to enhance their products with AI by using our Data Intelligence as a Service. Qualetics will be exhibiting at AI Expo Africa 2020, check out their booth for more information on their solutions. ai
COVID Project by SocialLab
SocialLab is a group of consultancy, research, and engineering teams dedicated to deliver unique intelligent solutions combining technology with social and human sciences, transforming social data into meaningful information By Ali Srour, CEO, Chief Data Scientist and AI Strategist at SocialLab
AN INTELLIGENT group of information monitoring solutions and platforms; a result of collaborative professional efforts, made for Social Good! More details
Solutions and more
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COVID Social dashboard is an interactive dashboard developed by SocialLab to help the world in understanding different insights about the novel COVID pandemic situation in order to manage, analyze, and monitor the effect of public social media microblogging news. Visitors may use this dashboard to build, filter, design, or export custom stories and aggregations based on their research.
Using Machine Learning (ML) and Natural Language Processing (NLP), SocialLab team conducted several deep analysis studies analyzing more than 70 different languages and measuring some of the hottest topics about COVID spreading pandemic. Find below some of the ready to use studies, and subscribe to be notified about any future releases.
COVID Discovery is a Google based website that covers useful information and tools that everyone might need to discover about the novel Coronavirus “COVID-19” (i.e. search trends and statistics by countries, recent news, public datasets, and recent academical publications) The website also contains a predefined Google Meta search engine to help researchers look for any topic in terms of COVID theme. MORE
Why is it important? pic 6
A professional intelligent lab that can be customized to fit any language and dialect, country or region, theme of interest, and data modules Learn More and Request COVID Intelligent Project by SocialLab is licensed under CC BY-NC-SA 4.0CC “We believe in the power of information intelligence and its role in defeating the current COVID-19 pandemic, and for that, we are launching this project for anyone to benefit from towards creating a better safer world” ai
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The provided solutions are as much important as any other treatment; it will help and guide governments and global health communities to perform solid defeating strategies against COVID19 pandemic. In addition, predicting regional death and new positive diagnoses cases and rates by correlating diagnoses statistics with the emotional and mental findings is a solid future contribution of the project
ass pro ides ﬁrst real-time
COVID-19 SCREENING solution both staff, visitors
For the foreseeable future, businesses will need to take precautionary measures against COVID-19 to protect their staff, contractors and visitors. As per government regulations, this includes a daily COVID-19 health-screening questionnaire and temperature reading of each person entering a building or facility.
SINCE APRIL 2020 as new regulations came to light, WizzPass extended the WizzPass System to provide the first complete digital system for businesses to have realtime COVID-19 monitoring across their buildings (single tenanted or multi-tenanted) for both staff and visitors.
The WizzPass staff-screening solution allows:
• Employees to be pre-screened before they arrive at the office through their own employee dashboard • Touchless on-site screening and daily temperature readings captured for each employee on the WizzPass workforce system • Automatic COVID-19 alert notifications sent to health and safety officers and risk department members for flagged responses and high temperatures • Real-time digital COVID-19 screening reports available through the WizzPass dashboard
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Pre-screening COVID-19 questionnaire
The WizzPass employee dashboard allows employees to perform a daily online pre-screening COVID-19 assessment to quickly self-report their health status before their arrival to work, and to save time when checking-in on arrival. The employee dashboard can be easily accessed via the employee’s mobile phone, laptop or PC (any internet-enabled device).
Various touchless check-in methods on rival
Businesses have various on-arrival checkin methods to choose from. If the employee was not able to perform the self-assessment before arriving at the building, they can still complete their assessment on arrival. Depending on the preferred process, businesses can choose which on-site check-in method suits each building the best: • Touchless WizzPass Security Scanner As the staff members arrives at the parking gate, building entrance, or reception area – security or health officers can make use of the WizzPass handheld scanner to scan the employee’s QR code on their “digital access card” (or do an employee lookup via email or employee number), record the employee’s answers to the COVID-19 assessment, mark if PPE requirements have been met (if required), and record the temperature reading for the staff member. Only once completed will the staff member be granted access onto the premises. The handheld scanner can be used at access-points such as parking or reception areas and can be used to capture additional details and take photo’s if required. • WizzPass Check-In tablet (with touchless check-in options) As the staff member arrives at the reception or security area, staff can make use of the WizzPass check-in tablet to check themselves in at the building (multiple checkin options available such as employee QR Code, facial recognition or employee lookup). Alternatively, the tablet can also be controlled by security or health staff to manage the check-in process with the staff member.
Automatic COVID-19 Alert Notifications
Should any staff member have any undesired COVID-19 screening results or have a temperature reading above a certain threshold, then email and SMS notifications are automatically sent to key personnel including the company’s COVID-19 committee, risk departments, security and/or health officers.
Real-time reporting, tracking, and segmented analytics All COVID-19 screening results can be viewed in realtime directly on the WizzPass dashboard to allow businesses to take the necessary action or precautions if there are any flagged results. All reports are also exportable and searchable using multiple filter options for ease of use and auditing or compliance purposes.
Easier COVID-19 contact-tracing and emergency response
WizzPass makes for easy contact-tracing in the event that a staff or visitor does test positive for COVID-19. The WizzPass system can also be used to see which other staff and visitors were on site during a certain date and time. Furthermore, if required an immediate emergency evacuation response message can automatically be sent by the WizzPass system to all personnel on site.
Used by various small, medium and large blue-chip businesses
The WizzPass web-dashboard can be used at security or reception desks by reception/security staff on a laptop, PC, tablet or smartphone. • Touchless self check-in through mobile phone The staff member can also use their own
WizzPass is already providing this efficient and robust screening-system to various small and medium businesses as well as large blue-chip clients across their building-portfolios. Health and Risk committees use WizzPass for real-time COVID-19 tracking across their business. Interested in also using WizzPass to protect your business? Please click here to get in touch or check out WizzPass’s booth at AI Expo Africa 2020. ai
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• Touchless WizzPass Reception Dashboard As the staff member arrives at the reception area, reception/security staff can use their WizzPass Dashboard at the reception/security desk (on their PC, laptop, tablet or smartphone) to select the staff member for check-in, record the employee’s answers to the COVID-19 assessment, mark if PPE requirements have been met (if required), and then check the staff member into the building. If a temperature reading is taken at this point, then this can be recorded on the dashboard for that staff member’s entry.
smartphone (can be linked to client’s employee app) to check themselves into the building, thereby allowing a further completely touchless checkin option. This check-in will then immediately appear on the security/ receptionist dashboard to allow for verification before entry (if required) and for input of the temperature reading.
If the staff member has not completed their daily pre-screening assessment, the system will automatically enforce the staff member to complete this on the check-in tablet (or on their own mobile device first) before being allowed to check-in to the building. If a temperature reading is taken at this point, and if PPE requirements need to be verified, then this can be recorded on the check-in tablet (or on the Receptionist Web Dashboard) for that staff member’s entry. The WizzPass check-in tablet comes standard with a secure stand which can be used to place the unit on any security or reception desk, or the unit can also be wall-mounted.
THE 4IRI MPUMALANGA
R ncubator -
Scaling up to UpSkill
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The Fourth Industrial Revolution Incubator (4IRI) is excited to announce its next step in their journey to capacitating South Africa with relevant and enabling skills. We will be offering training that will enable graduates to apply for their Remote Pilot Licence, which has been classed as one of the most exciting new additions to the aviation industry, Remotely Piloted Aircraft Systems, or commonly known as drones.
WITHIN SOUTH Africa, a survey was done on citizens wanting to complete their Remote Pilot License (RPL) and businesses hoping to acquire their ROC license or those hoping to renew their licenses. The new academy will be based in Secunda, Mpumalanga. Of this number, a quarter work for a company that uses drones, another quarter are self-employed or freelance drone pilots, and another quarter are self-employed in a line of work to which they added drones as a new service offering. About 5% work for a public safety department that uses drones, and about 4% are educators who are using drones in teaching. We have identified that many wish to apply for some kind of drone training, because they work in adjacent fields such as drone software, sales, maintenance, and counter-drone technology but are not themselves drone operators. 4IRI has identified and partnered with businesses who need pilots to operate drones within their industry. Specifically in mining, agriculture, film and photography, building and development surveying and so much more. With our corporate partners we will be initiating an internship programme for our drone graduates. Thus ensuring that after they have graduated and acquired their RPL, they have access to industry experience. The 4IRI Drone Academy will be launching in September 2020. Keep an eye on our website at www.4iri.co.za for more information and updates.
4IRI Digital Hub
The Fourth Industrial Revolution Incubator is launching its new Digital Hub in Nelspruit in September 2020.
What is a Tech Incubation hub?
So… The 4IRI is dedicated to the development of innovative ecosystems of a city by creating favourable conditions for localisation of high-tech companies. What this means, is we are looking to upskill the immediate community with technical skills that specifically meets the demands of the Fourth Industrial Revolution. We achieve this through incubating small to medium sized businesses. Incubation means we take your valuable ideas and business model from infancy to maturity over a duration of 2 years. Linking you up with key industry players who you can partner with or offer your services to. Additionally we have an exciting team of experienced industry experts who offer you mentorship and guidance that will enable you to meet and surpass industry standards. We have a hub in Johannesburg. But the tech being installed at the Hub in Nelspruit will be cutting edge, availing the right tools to your business to grow within the digital tech industry. The Tech Hub will be focusing on assisting individuals who have or are developing: • Software Development • Biotechnology • Blockchain Technology • Additive Manufacturing • Aerospace Technology • Artificial Intelligence • Drone Technology • Financial Technology The 4IRI Nelspruit Digital Tech Hub will also have a coworking space, that meets the Health and Safety Requirements during this crisis period. This space offers fast Fibre, an illustrious kitchen, brainstorm areas, smart boardroom facilities, the use of an auditorium for small events and a 30 seater coworking nest area. For more information on our Digital hub contact us via email@example.com keep an eye on our website for updates on our Nelspruit Digital Hub and Drone Academy Offerings. Visit the Fourth Industrial Revolution Incubator Booth at AI Expo Africa 2020 to learn more about its work. ai
APPLICATION OF REINFORCEMENT learning algorithms in automated portfolio
risk-reward decision optimisation
Of all the different types of machine learning fields, reinforcement learning (RL) is closest to artificial general intelligence, which can be viewed as the ultimate goal of AI evolution.
they offer an improvement over traditional portfolio optimisation methods that don’t use ML, these approaches have become popular recently. However, they suffer from the static nature of clustering which is drawback in usefulness. Supervised and unsupervised ML approaches do not offer the power of RL. With RL algorithms we can dive deeper and treat asset weight allocation not just as a one-step optimisation problem, but as continuous control of the portfolio with the delayed reward. This enables us to move from optimal allocation to optimal control in a data-driven world. RL systems do not have to make predictions or learn the structure of the market implicitly. They directly learn the most optimum policy (strategy) for changing the weights dynamically in a continuously changing market. It is not surprising that more and more recent experiments conclude that RL has the ability to significantly outperform index benchmarks, traditional investment portfolio optimisation methods as well as other ML algorithms. It can therefore be expected that RL will increasingly be used in the future for automated investment decisions. However, controlling algorithmic risk originated by AI systems, is also the most challenging for RL algorithms, given the complex architecture of RL solutions and algorithm opacity. Although many of the risks of RL solutions are similar to that of AI systems in general, tailored approaches are required to manage risks such as robustness, transparency, sampling bias, and data/concept drift to ensure RL solutions can be trusted. Whilst the potential investment outperformance of using RL can be significant, significant under-performance from their use can have negative reputational implications. To ensure that potential benefits of RL use are realised whilst downside risk is controlled, a systematic approach across the RL model life cycle is needed to address aspects such as: • fit for purpose algorithm selection and RL solution architecture design • reward signal features design • decision transparency, and • guard rails design As with AI solutions in general, controlling risk and ensuring trust in their use is a critical requirement for their ongoing use and benefits generation. RL is no exception and in addition has unique features that require a tailored approach to managing their risk and performance. Andre Blaauw will give a talk titled Optimising the risk-reward trade-off in portfolio management with Reinforcement Learning at AI Expo Africa 2020. ai
WHILE SUPERVISED learning deals with predicting values or classes based on labeled data and unsupervised learning deals with clustering and finding relations in unlabelled data, RL deals with how some arbitrary being (an “Agent”) should act and behave in a given environment. The way it is done is by giving the Agent rewards or punishments based on the actions it has performed on different scenarios. RL algorithms are evolving fast. Integrating deep learning techniques, these algorithms now incorporate advanced features, such as multiple agents inter-acting, experience replay, actor critic (one agent supervising decisions of another agent) to name a few. Open source development platforms, such as open AI Gym, further facilitate construction of RL systems. As RL borrows from other algorithms, developments in AI in general will benefit advancement of RL. Compared to other ML algorithms, they have substantially lager data requirements for training models effectively. AI and ML are disrupting decision making in many areas of finance. However, their most impactful applications relate to supporting or automating decision making in investment portfolio management. Big data challenges, such as increased connectedness of data, volume and variety, speed of dissemination together with the inherent noise and non-stationary nature of financial markets data have made it extremely challenging to realise attractive investment returns. It is a known fact that few fund managers outperform the market index. The key decision accuracy required for achieving acceptable returns is the allocation of weights of assets to be held in the portfolio over the investment horizon, which turns out to be an optimisation under uncertainty problem. Various traditional mathematical optimisation methods have been used for many years to solve this problem with limited success. With rapid advances in recent years, AI and ML algorithms can be used as an alternative to the traditional methods for optimal portfolio weights determination. For example, supervised learning algorithms can be used to predict asset price movements in the future and then these predictions can be used for the allocation of portfolio weights. Whilst sequence to sequence deep learning algorithms such as LSTM shows great promise in forecasting accuracy, the longer time horizon of investment decision presents a challenge for their accuracy. Alternatively, we can use unsupervised learning algorithms to group assets into some clusters based on their profitability, using hierarchical clustering algorithms, and allocate more funds on the most predictive ones and less on the opposite side. As
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By Andre Blaauw, Applied AI/ML IP Lead, Actuarial, Risk and Quants, PwC South Africa
LEVERAGING AGILE METHODS To Fast-Track Implementation of AI & RPA Technologies
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The COVID-19 pandemic has not only forced many organisations to fast-track their digitisation initiatives, but has also drawn emphasis on the need for efficiency in the face of limited resources.
IF YOUR organisation is looking to implement artificial intelligence (AI) and robotic process automation (RPA) technologies, you’ll want to join Ati Ngubevana’s talk at AI Expo Africa 2020. Ngubevana is the Group Executive Head of Department: Digital Process Re-Engineering at Vodacom where she is tasked with implementing intelligent automation across five African countries. Her talk at AI Expo Africa 2020 – titled “Successful extraction of AI & RPA” – will focus on how organisations can leverage Agile methodologies to fast-track the implementation of AI and RPA solutions. With an academic background in Financial Management, Ngubevana has over 10-years’ experience in the banking sector. Her working career primarily covers process efficiencies. “Through my exposure to Robotics Process Automation, I have been able to transcend over multiple industries like mining and telecommunications,” she says. Ngubevana says there are two reasons that come top of mind when it comes to failure in the implementation of AI and RPA technologies. “Their first point of failure is not having the right level of executive support which results in poor
change management. RPA should be positioned as technology that can be implemented in most business units, so it cannot have one particular BU function,” she says. “RPA has its limitations, so organisations fail to understand the true transformational journey comes with equipping the RPA team to have the capability to assess and implement intelligent process automation, not restrict it only to RPA,” adds Ngubevana. She explains that within her own organisation, Vodacom understands that traditional RPA has its limitations. “So we utilise multiple complementary technologies to ensure that we are enable our business to become more digital. This was not an easy ask, but this we have started to reap the benefits of an intelligent automation strategy, rather than an RPA implementation approach,” says Ngubevana. So what insights can delegates expect from Ngubevana’s talk at AI Expo Africa 2020? “You can expect a practical approach on how intelligent automation can be instrumental in an organisation’s digital transformation strategy. Having gone through the journey myself, there are plenty lessons learnt that I will be sharing,” she hints. ai
AI ETHICS As Data Science and AI practitioners, and organisations looking to adopt AI, we need to be aware of how systemic oppression and discrimination is represented within our data. It is important for us to identify problematic biases and tackle them head-on to ensure the products we put in people’s hands make their lives better.
Source designyourtrust.com While some results were humorous, one user highlighted that the AI was problematic when it converted an obvious photo of Barack Obama into a
white man. Other users had similar experiences when using images of non-White groups. The use-case for this face depixelizer was to extract facial features from data, however, what has been created is a model that places more emphasis on white features and works better on white people. This happened because the model was trained on a research dataset named FlickFaceHQ (FFHQ) which mainly consists of white people. The skew of white representation in datasets extends further than FFHQ and can simply be seen by googling “beautiful woman” which returns pictures of largely young, white females. This can lead to models working better for white people, for example, facial recognition. While the above are examples of how hegemonic whiteness is perpetuated through imbalanced data, more insidious is how minority groups are represented by models trained on bias data. In April this year, another experiment on Twitter went viral where
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Source: Twitter /@Chicken3gg
A BIAS model, statistically, is one that has learnt too well on the initial data that it cannot make accurate predictions on new, unseen data. This is the type of bias that Data Scientists often deal with and is a function of the model they’re building. The lesser dealt with bias, the bias with ethical implications, are the biases that exist within the data being used by the model and the biases of the person building it. We acknowledge that there is systemic oppression; by definition, it is encoded within the institutions we interact with daily and consequently in the data we are exposed to. Recently an AI tool designed to take pixelated photographs of people and reconstruct them into a more accurate picture was posted on Twitter
By Daniel Wertheimer, ata cienti t
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Source: Twitter /@bjnagel
Google’s cloud image recognition platform labelled an image of a black man holding a thermometer as a “gun” and the same image, when the hand was overlaid with white skin as a “monocular”. In a statement, Google said they found some objects were mis-labeled as firearms and found no evidence of systemic bias related to skin tone. However, without rigorous testing we can never know. Despite Google resolving the issue, it remains that if we don’t critique and understand our data collection strategy, models will learn to uncover bias that can result in problematic classifications based on race. This has far reaching implications for non-White groups. Data collection needs to be understood and scrutinised. In America, data shows that people of colour are discriminated by police more than white people. They’re stopped more frequently at traffic stops and police are more likely to use force against them. With the advent of predictive policing using this data, we’re seeing increasing amounts of black crime because police are now using bias, historical data to do their jobs. This, coupled with the collider bias of racist practices is not just perpetuating but compounding racial inequality. Some may argue that simply removing race as a variable will remove bias. However, if we remove race we cannot ensure racial parity within our data nor can we tell directly if our models are racially biased in themselves. Even with racial parity, you cannot
completely remove bias from your data therefore one of the objects of our models should be to optimise for fairness. Inequality exists in any data where there are protected attributes, be it age, gender, race or religion and optimising for fairness should be a requirement of your solution, not a nice-to-have. The solutions we are building have more of an affect on people’s lives than people’s lives have on our models. If we do not correctly address biases within our data, we’re only perpetuating these systemic injustices and further embedding them within our world. We need to understand that being unaware of how our data is biased will only perpetuate these problems. It is more important that we are aware of different biases so that we do not perpetuate them. However, it is not our job to solve issues related to bias but our job to raise awareness and have discussions with the relevant stakeholders to ensure that not only accuracy but fairness of our models is also important. It is important to train your staff to be aware of bias and make it a safe space for your staff to raise concerns. Don’t let bad people build robots. Daniel Wertheimer will give a talk at AI Expo Africa 2020 titled Growing a Data Science Team, From Legacy To Success. ai
AI FOR GOOD -
Time To Move The Needle
Artificial Intelligence (AI) has great potential to help us solve humanity’s biggest challenges. From climate change to clean energy to affordable healthcare and global pandemic response, the potential is there. However, our race to capture value from the technology challenges our ability to fully leverage AI to improve our quality of life and the world we live in. In order to use AI to make a difference, we must use AI for Good. by Fred Werner,Head, trate ic n a e ent i i ion at the nternationa Telecommunication Union
Moving the needle
The potential is undoubtedly there but we are running out of time... We have 10 years left to achieve the 17 SDGs and we need to act now to make this happen. AI solutions that we identify today need a few years to develop, a few more years to achieve scale and then a few years after that to achieve the desired impact. At a minimum, we are looking at a 10-year timeline, bringing us right up to 2030. We have to act now if we want a chance of moving the needle.
Scaling AI for Good
There is no shortage of innovative AI for Good applications and use cases. From using smart phones for early diagnosis of disease and pandemic contact tracing to robotics to increase agricultural productivity to using machine learning to increase cyber security and optimize telecommunications networks. However, it is one thing to develop a solution in a high-tech lab and another thing to deploy and scale these solutions across
Firing on all cylinders
We have reached a landmark where half the world’s population is online. While some might see this as an amazing achievement, the fact remains that 50% of the population is still not connected. This is the equivalent of a V8 engine only firing on four cylinders. We are not benefiting from the shared art, culture, music, creativity, knowledge, wisdom and potential problem solving power of half the planet. It is crucial that we connect the remaining 50% of the planet and so we can start firing on all cylinders.
The eye in the sky
How do we know we are making progress? This is a daunting task but approximately 30% of SDG targets could be tracked from space. For example, AI-powered satellite imagery analysis can be used to predict and prevent deforestation, track livestock with great accuracy, map poverty, provide data analytics for micro-insurance to small-hold farmers. This could be a game-changer, but no one is doing this yet as it requires massive scale collaboration and significant funding in the order of 1 billion dollars. If we cannot see the needle, we cannot move it.
Will we become more irrelevant?
AI is an extremely powerful technology that is not without its own risks and challenges. We must be vigilant that AI develops
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For example, AI can help: • 1.7 billion unbanked individuals gain access to digital financial services • Reduce 1.3 million deaths annually on our roads • Translate and educate in 2000 African languages • Lower public health costs for millions • Elevate the quality of data collection during pandemics without sacrificing privacy • Improve the quality and accessibility of civic services in overcrowded cities
developing countries, being mindful of harsh conditions on the ground and the societal, financial and political challenges involved. Connecting “problem owners” with “AI innovators” needs to be as easy as ordering an Uber if we are serious about scaling AI for good. We need to help people speak the same language and identify open algorithms and publicly available data sets to help them solve their challenges. The world needs an AI and Data commons as an enabling platform to scale AI for Good problem solving.
SO, WHAT is good? Different societies have different priorities, and a different understanding of what is “good”. So how do we know what global challenges to work on? That is easy... We have the United Nations Sustainable Development Goals (SDGs) to guide us. A set of goals to improve the quality and sustainability of life on Earth by 2030, agreed upon by 193 countries.
in a safe, secure, trusted and inclusive manner for all. We must be mindful of inherent biases already baked into our systems and avoid unintentionally codifying the worst of human behaviour into future algorithms. Will AI put us all out of work or even worse, make us irrelevant? AI experts themselves say that AI is too important to leave it to the experts alone. This issue affects every person, every company, every institution, and every government. It is imperative that we bring as many voices as possible to the table.
What do we want?
Through all of this, we should not lose sight of what is humanity, our own intelligence and what it is we truly want. It is often easier to blame technology, focusing on our fears and “what if”scenarios rather than discussing our core values and charting a beneficial path forward for humankind. If we do not know what we want for our future, how can we move the needle?
Many of these global challenges seem impossible and companies, institutions and governments alike do not have the means or the will to tackle them head on. We believe that solutions can come from anyone, anywhere. We need to find innovative ways to incentivise and mobilise the power of the crowd, combined with AI to unlock new breakthroughs and solutions.
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So where do we begin? The AI for Good Global Summit is the leading action-oriented, global & inclusive United Nations platform on AI. The Summit is organized by the ITU with XPRIZE Foundation, in partnership with 36 UN Sister Agencies, ACM and our strategic partner Switzerland. The goal of the Summit is to identify practical applications of AI to advance the sustainable development goals and scale those solutions for global impact. The Summit has delivered on its action oriented promise, giving rise to the AI Commons and generating numerous AI for Good projects in fields including education, healthcare and wellbeing, social and economic equality, space research, and smart and safe mobility. The Summit has delivered on its action oriented promise, giving rise to the AI Commons and generating numerous AI for Good projects in fields including education, healthcare and wellbeing, social and economic equality, space research, and smart and safe mobility. Additionally, the summit generated the new ITU Focus Group on AI for autonomous and assisted driving that will work towards the establishment of international standards to monitor and assess the performance of the AI ‘Drivers’ steering
automated vehicles. Work continues on projects that were ideated at earlier summits, such as the ITU Focus Group on Artificial Intelligence for Health (FG AI4H) with WHO, working towards the establishment of a framework and associated processes for the performance benchmarking of “AI for Health” algorithms.
All year, always online
Due to recent developments concerning COVID-19, the 2020 edition of the AI for Good Global Summit will now be presented as a continuous digital event, featuring weekly programming across multiple formats, platforms and time-zones, including keynotes, expert webinars, project pitches, Q&As, performances, demos, interviews, networking and more. We see this an opportunity to scale AI for Good and reach even more people, supporting our goal of being the most diverse and inclusive platform around beneficial AI. With a wider and more inclusive reach, as well as year-long visibility, our new format provides partners, speakers and supporters a much larger, more visible opportunity to connect problem owners with AI problem solvers and work together on actionable projects that shape the future of AI for Good. The digital edition of the AI for Good Global Summit has already begun with the launch of the AI for Good Webinar series, AI for Good Innovation Factory, weekly AI for Good artists and more. As the year progresses, the Summit will make its way through the many confirmed AI for Good sessions and speakers from the 2020 Summit programming as well as tackle more region-specific content.
The time is now
• Act - Create practical AI for Good solutions aligned with the SDGs through the breakthrough sessions and innovation factory • Scale - Use the Global Initiative on AI and Data commons as an enabling platform to scale AI for Good • Connect – The remaining 50% of the world to fire on all cylinders • Be vigilant - of inherent biases, safety and security risks • Monitor - real time tracking of our progress towards the SDGs • Humanise - Focus on our own intelligence and what we really want for our future • Move the needle - Employ innovative problem solving methods to bring about radical breakthroughs for the benefit of humanity • Join the Movement! – and help shape the future of AI for Good Fred Werner is one of the keynotse speakers at AI Expo Africa 2020. Learn more here aiexpoafrica.com ai
AI: AFRICA SHOULD not be left behind
Data is the new oil, AI is the new electricity… it is deployed everywhere, in all the sectors of our life, from finance, to healthcare, to education to defence, etc. All our devices, businesses and lives will have AI components. The AI will assist us, entertain us, cure us, feed us, drive us, and much more. AI will be in every corner of our daily life and we should prepare our current and next generation to deal with it in an ethical way.
However, there are a number of barriers that will keep Africa lagging behind in the AI race, if not addressed. Infrastructural challenges, data gaps, highly skilled labour needs, and poor regulatory environments are still inhibiting people’s ability to harness AI across Africa. There is urgent need to enhance the strength and agility of educational systems to meet new digital opportunities, and support investments in learning outcomes in the areas of machine learning, artificial intelligence, and data sciences in Africa. We should target and invest in youth at the primary school level, offer mentorship programs for emerging leaders, including for women and girls to build the next generation of AI practitioner. There is also need to fill data gaps in Africa. Data is fuel AI : the more data is available, the better and more effective results this technology will deliver. However, for many African countries, access to large sets of data is limited. Therefore, solutions must be found to help Building an inclusive AI future in Africa I think, in an exponential future, we need to accelerate the pace of development and implementation of AI strategies in Africa to catch-up with other nations; otherwise we will lose the global race. We live in an exponential future, which will be run by AI. By 2030, artificial intelligence (AI) will add $15.7-trillion to the global GDP, with $6.6-trillion projected to be from increased productivity and $9.1 trillion from consumption effects. The innovation ecosystem in Africa is taking shape; African countries have to be a big player not as an AI consumer but AI producer. We need to join the crowd, we need to take action NOW. Africa cannot and should not be left behind. ai
MANY NATIONS are racing now to be an AI global leader, we see the battle between superpowers China and USA which are in the forefront of the global AI race. Other nations are following, we have collected 50+ AI national strategies in the world so far, some are finalised and others still under process. Tunisia was the first African country to think about the development of an AI strategy. It has created an AI Task Force and Steering Committee to develop a national AI strategy. The primary goal will be to facilitate the emergence of an AI ecosystem that acts as a strong lever for equitable and sustainable development and job creation. The objective also is to facilitate the emergence of AI leaders companies able to develop AI applications connected to people and their needs on the ground (The ground-up approach). The potential benefits of AI translated into real impact for people. It is not a matter of a copy-and-paste of “made-in-theNorth” AI policy frameworks. In Tunisia, we are working on developing a public-private partnerships to design and deploy AI applications that could help increase access to healthcare and education, energy and improve government efficiency. We already launched many projects mainly during the coronavirus sanitary crisis. These initiatives were conducted with collaboration of a network of startups, universities, research centres, and public institutions for the development of smart and sustainable solutions. African countries should develop their own AI specific policies and strategies over the next coming years to build policy capacity as well to help design AI regulatory frameworks fit for the African context. Many African countries have already started thinking about AI strategies, such as Kenya, who has finalised its strategy.
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By Kais MEJRI General director of inno ation an techno o e e o ent ini tr of n tr an ni ia
SMART SOCIETY — What’s in it for South Africa?
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AI Expo Africa speaker Lebogang Martins, IOT Specialist Project Manager, talks about the need to justifying the benefits to society of next generation technologies, such as the Internet of Things (IoT), artificial intelligence (AI), 5G, data science, algorithms and analytics, to bring new and significant value to its citizens.
EVER SO typically a society finds itself at the crossroads to transformation and must ask themselves key and pertinent questions including the following. Can South Africa seek to enable next generation technologies, algorithms and analytics, to bring new and significant value to citizens whilst transforming its buildings and cities into an advanced smart society that is more resilient, safer, healthier, economically vibrant, and attractive to their residents, businesses and visitors? Considering the economic drivers together with political unrest, social health pandemics, will we be able to weather the process required that involves building a smart society one block, one park, one building, one neighbourhood, one community at a time? Will we be patient enough to see the process through especially as it’s a complex multi-decade undertaking irrespective of whether one approaches it from a
By Lebogang Martins, IOT Specialist Project Manager, IoT.nxt
top-down or bottom-up approach? While the benefits and Return on Investment (ROI) of smart buildings and cities are well documented, what would be the value to South Africa and why would it even be a consideration for diverting private/public funding to encourage the development and retrofitting of smart buildings and cities to building a smart society?
The cities must rock …
The macro-environmental composition of South Africa is very dynamic with diverse constituents and complex geographical, economic and political needs even when considered by provincially. In order to understand how a smart city enabled society will benefit Mzansi requires an appreciation of some background fundamentals and understanding of the drivers of civic value including its care abouts’ & outcomes, power
A smart society and its cities viability should not be measured in the context of businesses those key metric is ROI, but instead must seek to improve its adoption of strategic imperative that make conducive to live and operate in especially when compared to similar structured cities i.e. ROI based on financials and also for a smart society’s initiatives and programs leading to a place that is healthy, productive, safe, self-sustaining and attractive over time, and where citizens and businesses choose to live and operate in. taking a smart building as an example, these outcomes can therefore be classified as either: • Outcomes arising as a direct consequence of implementing the smart society initiative e.g. when a building transitions
to a digital whole-building energy management system, the immediate benefit is a reduction in the energy consumed, and thus the savings in energy bills. • Outcomes arising as a indirect consequence of implementing the smart society initiative e.g. new skills and personnel required to support the smart building technologies, which stimulates the economy local economy by creating the need for new jobs and a smart building business ecosystem to support and service the smart building. • Outcomes arising as a consequence of innovation and are created from transformational opportunities created by the implementation of smart building infrastructure and capabilities e.g. the smart building makes its excess energy and communications capacity and capabilities available to the city, which in turn can be used as a smart city hub for hosting various communications and sensors for city use. For more on the topic of smart societies, cities and building please join us at AI Expo Africa 2020. ai
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… and for the betterment of the people The South African government is a creator of civic outcomes, but it is not the only one. Civic outcomes are created, delivered and maintained by a ‘provider ecosystem’ of groups that includes national & quasi-government, municipalities, parastatals companies, communities and citizens with each group responsible for delivering outcomes within its scope and domain. A general oversight is that smart building is also an outcome provider to society as it creates those outcomes that cities care about with less cost, greater efficiency, and less resources. For example, the municipalities are responsible for such things as maintaining streets, traffic signals and parks, while quasi-government companies are responsible for water and electricity. This provider ecosystem is intended to work collaboratively to deliver certain outcomes that are truly for the betterment of society. Supporting these provider ecosystems is an infrastructure
comprised of people, organisations and businesses, policies, laws, processes and technology integrated together to create the desired outcomes. The responsive civic ecosystem is adaptive, agile and always relevant to all those who live, work in and visit the cities. Whilst utilising advanced digital technologies, such as robotics process automation, IoT, artificial intelligence and analytics, and integrated into this underlying infrastructure, new disruptive and transformational civic outcomes are created.
centres, and how the value for these outcomes is quantified and evaluated by its citizens. Ultimately, these interconnected outcomes must lead to the ultimate overall ROI for each and every city in South Africa – a place that is healthy, productive, safe, self-sustaining and economically conducive, and where citizens and businesses choose to live and operate in. A smart society built on its intertwined backbone of cities is in the “business” of creating and maintaining civic outcomes for its residents, businesses and visitors. These include better government throughput and ease of doing business; public safety and welfare of its people; a higher standard quality of life; mental, physical and social health and wellbeing of its people; ease of transportation, transit and traffic management; sustainable environment, energy, water, and air quality management processes; and most importantly its economic opportunities. While all cities care about these outcomes to a certain extent, some outcomes are more relevant to them than others. Each city is unique, and its focus on specific civic outcomes reflects its unique economic, geographic and political priorities, and the needs of its many constituents. These civil outcomes are for the betterment of South Africa’s cities, municipal utilities, private and public companies, communities and its citizens as a whole.
HOW TO BE THE How to Be the Disruptor Using AI by Neil Sahota
Disruptor Using AI
From newly founded startup company to Global Fortune 500 juggernaut, they are all asking the same question: how can I disrupt my industry by using artificial intelligence (AI) capabilities? The answer is think differently. The problem, though, is nobody teaches how to think differently. Most people assume it is that chance moment of epiphany where suddenly the universe becomes clear and the “ah-ha moment” arrives. do you teach that? Regrettably, when it comes to AI, this problem500 becomes compounded. FromHow newly founded startup company to Global Fortune juggernaut,
People often believe AI either is incapable of doing something or cannot believe the machine can perform
they are all asking the same question: how can I disrupt my industry by using artificial intelligence (AI)Thankfully, capabilities? is think differently. think differently is severely constrained. we canThe breakanswer through these barriers by using two
the task as well as a human can. Consequently, when it comes to being disruptive with AI, our ability to frameworks: 1) Neil’s Magic Formula, and 2) TUCBO™.
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By Neil Sahota, a ter n entor nite ation rtiﬁcia nte i ence i or rofe or at r ine an a thor of the oo n the . . e o tion.
about AI capabilities, it does not solve the challenge of thinking differently. This is where TUCBOTM comes into play. TUCBOTM stands for: THINK DIFFERENT (Ideation), UNDERSTAND DIFFERENT (Develop), CREATE DIFFERENT (Enable), BE DIFFERENT (Actualization), OWN DIFFERENT (Normalize). When it comes to AI, TUCBOTM gives enterprises the THE PROBLEM, though, is nobody teaches how to think framework and the techniques, differently. Most people assume it is that chance moment of models, and tools to create viable ventures with meaningful, To free our minds AI limitations, we need tobecomes employ Neil’s Formula.value-add This starts innovation with establishing epiphany whereofsuddenly the universe clearMagic and the with an executable, disruptive idea. the right mindset and thinking about “blue sky” possibilities. Whether an AI system can do work is differently, and TUCBOTM gives us “ah-ha moment” arrives. How do you teach that? Regrettably, The first stepthe is to think when it comes to AI, this problem compounded. immaterial (for now.) This is an ideationbecomes exercise where create the entrepreneurial mindset. techniques. We must stepFirst is repurpose or multipurpose. two powerful People believe either is incapable of doing something This means looking atOnce an existing AI solution and seeing if away fromoften thinking aboutAIwhy something won’t work and focus on how to make something work. cannot believe the canweperform the task well as the real it can becauses applied to a different industry. For instance, using inor this mentality, focus onmachine the problem want to solve andas understand root behind it. a human can. Consequently, when it comes to being disruptive AI psychographic profiling capabilities is a staple for digital We also must apply domain expertise to understand constraints, like regulations, and potential adoption with AI, our ability to think differently is severely constrained. marketing. However, based on this success, it has been Thankfully, we can break through these barriers by using two repurposed in human resources to improve the recruitment frameworks: 1) Neil’s Magic Formula, and 2) TUCBOTM. of employees who are a better team fit for the enterprise’s To free our minds of AI limitations, we need to employ Neil’s corporate culture. Second is to challenge assumptions. Magic Formula. This starts with establishing the right mindset Assumptions are not facts, but they are believed for so long that and thinking about “blue sky” possibilities. Whether an AI system we hold them as truths. Artificial empathy is a great example of can do the work is immaterial (for now.) This is an ideation challenging assumptions. Humans are emotionally complex and exercise where create the entrepreneurial mindset. We must dynamic people. To read the constantly changing emotional step away from thinking about why something won’t work and state of a person in real-time and response accordingly is focus on how to make something work. Once in this mentality, something only another human can do. Well, companies like focus on the problem we want to solve and understand the real Cyrano.ai have challenged this assumption. They have shown root causes behind it. We also must apply domain expertise to that AI can often be just as good as (and sometimes better) understand constraints, like regulations, and potential adoption than a person. An AI system can read every point that sends a challenges (i.e. reasons why people may resist solutions.) This non-verbal communication simultaneously. For example, when creates the “art of the possible” or the opportunity. Then we a person lies, there are over 2,000 points on the face alone marry the opportunity with technical expertise to validate if that reveal this. In parallel, the AI can also detect voice tone an AI can perform the functions or not. Thus, we avoid any inflections, word choices, and review biomedical data (if it has it.) implicit bias we might have on what machines can and cannot That’s way more data than a human can process in real-time. do during the ideation stage. In conjunction with the technical By leveraging Neil’s Magic Formula and TUCBOTM, any expertise, we also must look at infrastructure requirements person can generate those “ah-ha moments” No longer will luck (e.g. network speeds, computing power) to see if a technically be the deciding force. Instead, we have a reusable framework in feasible solution can be supported. This gives us the “possible” which we can identify meaningful, disruptive solutions using AI. or solution. We no longer have to wait for the disruption, we can create the While Neil’s Magic Formula helps break the limited thinking disruption. ai
to predict consumer
behaviour post-COVID-19 The COVID-19 pandemic has forced the consumer preferences and behaviour to change in an era of great uncertainty and consumer nervousness about the economy and their own future. We are seeing a pattern shift in the way we consume and think about consumption, leading to a change in buying behaviour. Many of these behavioural changes may turn out to be permanent. At the same time, supply chains have received a significant shock and have seen unprecedented demand for – and mass stock outs of – essential items. By Nella Oluoch, CEO at Keypetbooks
• Build immediate response capabilities with suppliers: Organisations should adapt their supply chain and work closely with their suppliers to ensure an aligned and scenario-based business continuity plan is in place to frequently assess evolving scenarios, adequate
• Partner with delivery platforms Leveraging the established delivery ecosystems for their fleet network to avoid delayed deliveries. Once the pandemic is over, consumers will be more cautious about cleanliness, health and safety. Consumers will also shift to brands that show higher levels of product safety and some consumers will prefer local products. Technology will be key for both the recovery phase – and also for the longer-term, relaunch phase. Technology will be key to future-proofing the organization for a new reality and therefore, consumer products companies, retailers, and restaurants will need to combine technology with an understanding of societal sentiments, giving importance to a greater purpose and sustainability to people. In the long-term, being highly responsive towards consumer trends will be critical, and companies that will automate predictive analytics for consumer behaviour will be the ones who will best match offerings and demand. ai
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• Focus on realigning product categories: Organisations need to continuously reassess consumer preferences and align categories and offers accordingly. This requires agile demand planning and clear prioritisation of focus areas and resources. Unilever says it is currently focusing on meeting a surge in demand for food and refreshments and concentrating on larger SKU items – such as large jars of mayonnaise rather than smaller containers.
supplies are on hand to meet demand along with a buffer stock of essential items, agile approaches are in place to handle logistics and fulfilment of online orders, establishing communication and data-sharing channels with their suppliers and consumers to drive flexibility and transparency, exploring different fulfilment centres for online orders etc.
INTERACTION WITH physical stores has taken a heavy toll and online interaction is accelerating. The COVID-19 pandemic has accelerated the significance of online channels with more and more consumers considering online as their primary shopping. Although traditional organizations have been improving their online capabilities in recent years, today’s unprecedented situation has placed significant stress on online channels. For example, food retailers in some countries have struggled to meet order demand. Core operational agility and resilience is now a priority and several action points have been highlighted. Companies need to:
AI IN HR Headlines over the past few years have focused on the doom and gloom part of AI: robots will be taking over our jobs or machines and systems that we wonâ€™t be able to control could backfire on us.
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By Ronnie Toerien, rac e e e o ent Strategy Leader â€“ Africa
THIS FEAR of Artificial Intelligence is actually very similar to what was experienced at the start of the first Industrial Revolution many decades ago. People were concerned that they would lose their jobs and become redundant with the introduction of machinery into factories. What really happened was that the factory workers learned how to work the machinery and very few, if any people, lost their jobs. Interestingly, it is no longer just manual routine functions that will be taken over by machinery but new technologies such as Machine learning, IoT and Robotics will replace even high-level work such as Lawyers and Financial Advisors with the ability to rapidly sift through data lakes of information to find solutions to problems. Having said that, the reality is that AI is not going to take over our jobs but rather augment the tasks we already do to make organisations more efficient and effective in meeting the demands of todayâ€™s world. The trick is going to be trying to figure out the correct combination of people, data and machines to optimise business processes and increase productivity and therefor profitability. Technology has always been a part of achieving business outcomes, driving greater efficiency and optimisation. Artificial intelligence is about to change how humans interact with technology for the better. AI can enable organisations to realize the full potential of talent management by creating an environment that meets employee needs and improves retention. Such technology can personalize career development, optimize succession planning, close skills gaps and steer compensation strategy - supporting leaders and managers in developing and deploying talent, which in turn creates strategic advantages for the business. For example, AI can equip an employee with intelligent suggestions for courses or reading that will aid in their day-to-day job duties. As a positive deviation from the traditional one-size-fits-all approach, employees will feel the difference in an experience that accounts for
their personal goals, needs and well-being. Organisations will find investing in employee growth and satisfaction easier and more effective. According to the AI at Work global study conducted by Oracle and Future Workplace in 2019, 64% of people would trust a robot more than their manager and half have turned to a robot instead of their manager for advice. In the survey, 82% of the respondents believed that robots could do certain types of work better than their boss can. They felt that managers are better than robots in activities like understanding their feelings (45%), coaching them (33%), creating a work culture (29%), and evaluating team performance (26%). But robots are better than human bosses at tasks such as providing unbiased information (36%), maintaining work schedules (34%), solving problems (29%), and managing a budget (26%). With AI transforming the relationship between people and technology at work as well as that between employees and their bosses, traditional assumptions about what managers do and what they should be doing are being called into question. These differences have important implications for how organisations can get the most value from line managers, as well as how they can best attract, retain, and develop talent. For instance, managers who let AI handle more administration-related coordination and control tasks may free up time, mental bandwidth, and energy to interact more directly with their employees. The world of work is constantly changing as emerging technologies provide organisations with greater efficiency and allow them to innovate and explore new potential. However, the unprecedented events in 2020 have been like lighter fluid on an open flame regarding business transformation. With mandates to work from home if possible, the disruption of traditional business models is being driven by pure necessity. Human Capital Management (HCM) has a vital role to play in ensuring business continuity
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bring together information and related components that do not naturally connect. For example, analytical tools can be combined with a combination of absentee data and workforce plans to model scenarios and combat skill gaps. The value that a great HR executive can bring to an organisation today is enormous, from preventing the loss of reputation to boosting worker engagement and productivity, to being the moral compass of an organisation. To do that effectively, HR executives will need to develop a deep understanding of AI, both in terms of how it’s changing the workplace, and in how it is changing the nature of the HR function itself. Rather than being afraid of the new world of work, HR executives will need to embrace the changes and put technology as a central tenant of their HR Strategy. It’s no longer enough for HR to have a “gut feel” about how things are going – just like other parts of the organisation, HR needs to be data led. Because this is becoming a data-driven function, HR Directors will need to build great relationships with people who know technology in their organisations, and with experts outside as well. They will need to have conversations with their peers in IT and Operations, so that decisions about technology across the organisation are made in ways that ensure HR’s needs are included. The skills that an HR Director needs today have changed. If you don’t understand the value of combining People, Data and Machines, you’re in the wrong job. ai
and resilience as we march into the new world of work. With employees scattered, the data collected, and analytics generated by next-generation HCM solutions become crucial to combat absenteeism, identify atrisk individual employees and formulate a succession planning strategy across an entire organisation. The current crisis will also have a major impact on talent acquisition and retention, which will have a knockon effect for business delivery. Reassurance through empathetic communication is essential. Empowering employees with information about the company’s strategy during this period, as well as providing open channels for two-way conversation, will give people a sense of belonging to an organisation that is looking after and listening to them. Going hand in hand is the need to help grow employees. Learning and development are often hammered when enterprises embark on crisis costcutting, but the current climate is the perfect opportunity for HR to equip staff for new roles or take advantage of employee skills and use them in new ways (possibly with “gig economy” opportunities) that support the organisation, and the individual’s own professional growth. The new world of work is also notable for its drastically altered business processes. Older ways of working are often proving too inflexible to overcome current challenges. Cloud HCM plays its part in breaking down rigid division, not only between departments but data sets as well. As a powerful integration tool, it can
New Advisory Board
GirlCode, a non-profit which aims to empower girls through technology announced in early August that it has appointed a new seven-member advisory board which will provide the organisation with strategic oversight and guidance. GIRLCODE SEEKS to get more women involved with technology, design, development and leadership under the belief that the more women are included in these fields, the more successful and diverse companies and their products will be in the future. The organisation — which was founded in 2014 by chairwoman Zandile Mkwanazi — aims to empower 10 million women across Africa by 2030.
The new GirCode advisory board is made up of members with established backgrounds in tech who’ve worked for companies that include Uber, Nelson Mandela University, Accenture and Virgin Media UK. They are Bontle Senne, Dudu Mkhwanazi, Neroshnee Rangasamy, Nonkululeko Tsita, Thato Mabudusha, Venisha Nayagar and Philani Mdingi. ai
SA IDENTITY VERIFICATION
startup iiDENTIFii announces L.America expansion
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Cape Town based identity verification startup iiDENTIFii in May announced that it is expanding its services to Latin America.
IiDENTIFii WAS founded in 2018 by Lance Fanaroff, Robert Sussman and Gur Geva. The firm offers enterprise-grade software development kits (SDKs) for mobile phones, tablets and web browsers to enable face authentication, biometric liveness detection, ID document capture, and data extraction. IiDENTIFii’s clients include Shyft, Standard Bank and Bidvest. The company said in a statement on its website that it is ready to deploy its golden triangulation identity authentication technology to its new partners in Mexico, Mexico City, and across Latin America. “iiDENTIFii innovators have spent close on 5 years coding their robust technology which augments on-line and offline identity, proves liveness of a remote individual and
then tokenizes the proof of liveness. iIDENTIFii have proven their optimal accuracy rates on massive data sets and are recognized for being a company that both merges online and offline identities as well as secures them, regardless of geography or ethnicity,” the firm said in its statement. The firm added that, having worked in Africa, Asia and Latin America, it is deeply aware of the versatile needs of these complex markets. “Considering the complexities of indigenous data sovereignty, iiDENTIFii has expanded its global infrastructure to the Microsoft Azure Cloud, allowing for the deployment of their technology in Latin America to be seamless and concise,” the company added. ai
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