SCS Magazine 2021 Issue 2

MCI (P) 068/04/2021

IT’S ALL ABOUT TRUST 02 Is Technology Trustworthy, Morally Equitable and Ethically Acceptable?

04 What Role Does Developers Play in Building Digital Trust?

06 Can AI Really Resolve the Disruption Challenges in the Retail Industry?

08 Lee Joon Seong Chats about the Advantage AI Is Giving Your Business 10 Prof Lim Sun Sun Analyses Whose Job It Is to Inspire Trust in Tech

Issue

02 2021

Contents Vision To be the leading infocomm and digital media professional society in Singapore

EDITOR’S MESSAGE

POWER BOOST

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Why Digital Trust Matters?

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How Can Computers Earn the Trust of Humans?

THE BIG IDEA 02

Mission 04

Lead the Way To lead and contribute to the vibrancy and growth of Singapore’s infocomm and digital media industry

Add Value To add value to the infocomm and digital media professional’s career and personal development

Be the Voice To engage and be the voice of the infocomm and digital media community

How to Build Digital Trust?

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Is Technology Trustworthy, Morally Equitable and Ethically Acceptable?

What Role Does Developers Play in Building Digital Trust?

Can AI Really Resolve the Disruption Challenges in the Retail Industry?

#LATEST@SCS 17

AI Ethics and Governance Grows in Importance in Singapore

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Put in Your Nomination for Tech Leader Awards 2022

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Join Us at Splash Awards Finals!

GEEK SPEAK SPOTLIGHT 08

Lee Joon Seong Chats about the Advantage AI Is Giving Your Business

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Prof Lim Sun Sun Analyses Whose Job It Is to Inspire Trust in Tech

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Are We Trusting Too Much?

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The Magazine of the Singapore Computer Society

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FROM THE EDITOR’S DESK

9:41 AM

Digital Trust: It Takes Years to Build, And Seconds to Blow Up

T

ry naming one similarity between “tech” and “trust”. Yes, both are spelt with a “T”. But that’s hardly where their similarity ends. Trust takes years to build. Likewise, it has taken years for tech to arrive at this point.

What’s more interesting is, we are now at the nexus between trust and technology. And to move forward or stay ahead, it is not about either-or but both-and. As the insider, Mr Lee Joon Seong from Accenture, says “Artificial Intelligence (AI) has become table stakes for businesses seeking competitive differentiation.”

And indeed, we’ve seen first-hand how AI helped normalise demand-supply during these abnormal pandemic times.

Exciting as it sounds – we are just grazing the surface of possibilities. Tech, and more specifically AI, can only do more if there’s good data. Privacy issues aside, the key to more and better data lies in – trust.

questions – and no definite answers. We’ll do well to remember that tech is neutral – it is not judgemental. Hence if it is biased, it is because of the people who design and build it.

That’s why a rigorous DevOps and, as Prof Lim Sun Sun from SUTD astutely points out, the education of tech designers and developers in ethical issues matter. Of course, the importance of a strong and transparent professional ethics framework such as AI Ethics and Governance Body of Knowledge cannot be undermined too. After all, it takes the whole village – tech companies, governments, developers, tech users – to build a trustful digital ecosystem.

We are now in the second half of the chessboard for Moore’s law, and whether we like it or not (or trust it or not), the level of trust we have in tech will decide its course and speed of development. Trust me – it’s all about trust.

Happy reading!

How much we share our data depends on how much we trust tech companies, their applications, and the governance system.

Can I trust tech companies with my data?

How is my data used? Is my data potentially exploitable by software vulnerabilities? So many

EDITOR Tan Teng Cheong CONTRIBUTING WRITERS Eu Kwang Chin Khoong Hock Yun Vladyslav Koshelyev Albert Ooi Harish Pillay Cherie Teo EDITORIAL SUPPORT Claudia Lim

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EDITORIAL & DESIGN Lancer Design Pte Ltd

TAN TENG CHEONG Editor Fellow, SCS tan.teng.cheong@scs.org.sg

FEEDBACK We value your feedback for this magazine. Simply email scs.secretariat@scs.org.sg with your comments to help us produce an even more interesting and relevant magazine for you in subsequent issues. You are welcome to submit articles for inclusion consideration.

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All views expressed by contributors are their own and do not necessarily reflect the views of the Society.

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02

THE BIG IDEA

THE IT SOCIETY / Issue 02/2021

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What’s Tipping the Balance in Trust, Privacy and Ethics If Tech is Unbiased?

HARISH PILLAY Fellow, SCS Head, Community Architecture & Leadership, Red Hat

One often quoted statement is: “technology is neutral – it is not judgemental”. If we accept the preceding statement as reasonable, does it mean that we deem technology to be trustworthy, morally equitable and ethically acceptable? Let’s tease out the issues in this multilayered question.

M

ost technology is arguably neutral.

Take nuclear technology for instance: it generates electricity; it is used in cancer treatment; it also powers spacecraft that enable humanity to explore the universe. Yet, it is one of the most dangerous weapon systems.

Likewise, for water. Life needs water. But too much of it drowns life and too little of it causes death; water in its hot gaseous form can scald while water in its cold solid state can freeze life.

Again, water as a technology, is neutral. Like nuclear technology, water does not take a stand.

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THE BIG IDEA

03

OUR TRUST IN TECH IS SUPERFICIAL. Now, take a moment to consider the technology today. The third law of “Clarke’s three laws” says that “any sufficiently advanced technology is indistinguishable from magic”. True enough, it is hard to explain to someone from as recent as the early 20th century what technology can do today.

On numerous occasions, and in many different cities, I have been told: “I have nothing to hide so I am not too concerned with privacy when it comes to technology.” To these individuals, I always pose the same cheeky question: “I know exactly what and how one does what one needs to do in a restroom – i.e. it is not a secret. And yet, why does one close the door?”

Case in point, imagine having to explain to our great-grandparents that at a flick of a switch, we can see someone behind the wall or halfway around the world. It will involve detailing the structure that has to be put in place – the device; electronic wiring; silicon mining; physics; manufacturing, transport and business processes; and international shipping and manufacturing agreements – as well as the engineers’ training and education to make that “one flick of the switch to speak or see someone” possible.

Of course, it is all in the name of privacy. Privacy is a fundamental part of the human condition when we can understand the implication but not how it applies. To illustrate this, take a moment to think about public spaces such as parks, the streets and public transport. When cameras in these public spaces take our photos or videos, we don’t immediately ask questions. We assume that they are taken for a legitimate reason, and trust that they are operated and managed by authorised entities. We are not certain if we can request for a copy of our images/videos taken by cameras in these public spaces, or their deletion.

Even after all that explanation, it still doesn’t quite tell the whole story about the trustworthiness of the entire process. Can we trust that the technology is safe for use? Is it safe to hold the device next to our head (in case there is electromagnetic radiation)? Can we trust that an unauthorised person will not gain access to that connection? Is it important for the communication to be encrypted? If it is, how can we ensure that the communication is encrypted? Do we understand the mathematics behind symmetric encryption?

The truth is – preceding questions address the trustworthiness of tech at only a superficial level.

THE VALUE WE PLACE IN PRIVACY DIFFERS. Switching lens, let’s look at privacy. What issues surround privacy where technology is concerned?

It’s worth noting that humans are the only beings with the notion of privacy.

Comparatively, non-humans do not exhibit concerns about privacy in any perceivable way.

Interestingly however, we cannot agree on what constitutes privacy.

ETHICAL OR UNETHICAL IS A FINE LINE. Suppose the public transport we take passes a home that has a camera trained on the street and the ability to capture our image on the public transport, do we have the right to ask that person for a copy of it and its deletion?

What if that person is a software developer who wants to test the efficiency and accuracy of his algorithm in facial recognition from a real time camera feed before its actual deployment at a high human traffic point, like a border crossing?

Suddenly, the use case seems to be fair and quite acceptable.

But we will never know – that same algorithm could also be deployed by the government to pick out and track targeted people for some less than noble reasons (like ethnicity, etc.). Do we then have the moral and ethical right to object to the use of our creation? Perhaps we do. But even so, it doesn’t necessarily imply that we can prevent misuse.

This brings us back to the start. Technology is neutral – its use or misuse is what determines how it tips the scales of privacy, trust and ethics.

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THE BIG IDEA

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If Anyone Can Inspire Digital Trust, It’s Us – Developers

In the world of big data and Artificial Intelligence (AI), digital trust underpins continued growth and development.

However, building a strong, reliable, safe and secure digital trust ecosystem is no easy matter. No free rider is allowed – regulators, tech companies, consumers, and at the heart of it, ethical DevOps are all essential.

THE IT SOCIETY / Issue 02/2021

ALBERT OOI Lead IT Architect, Applications Services, NCS Group

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ut with everyone in DevOps talking about being agile, and failing fast and learning fast today, where does quality stand? How can we strike a balance between speed and quality? Or what measures can we put in place to harmonise them?

IT ALL STARTS WITH SECURED AND QUALITY SOFTWARE Typically, two approaches are most commonly applied in ensuring software quality – do quality checks after the design and development cycle, or continuously throughout the development phase. While the former is a common practice traditionally, the latter typically offers fewer problems and surprises at the end.

WHY SECURITY SHOULD NOT BE AN AFTERTHOUGHT By starting small, chewing little, validating, testing and then progressing a little more, it fits the ideology of fail fast and learn fast. And even when nothing fails, insights gained can help optimise long term goals, and move the development along. In a nutshell, this is shift left security.

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Contrast this method with waterfall monolith applications where testing is only conducted at the end. Not only is it likely that we will end up with a long list of issues that need fixing, we may also have to redesign modules or patch in complex workarounds to resolve issues that could have been circumvented totally if checks were conducted earlier.

That’s not a great way to design – obviously.

THE CASE FOR SHIFT LEFT SECURITY You’ll ask – what then is a better approach for DevOps? Well, take a Jenkins build pipeline that churns out software sub modules. We’ll want to embed quality checks into every pipeline processing each software sub module and deal with arising issues incrementally instead of having a surprise when codes are assembled and run.

THE BIG IDEA

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Try imposing this concept into a manufacturing line setup that runs from left to right. Quality checks should be implemented as much left as possible and practical before the final code assembly comes – in other words, shift left the quality checks. If issues can be detected early, they can be fixed early. Importantly, costs of rolling back major design decisions and architecture rebuild can be avoided.

HOW TO MAKE SHIFT LEFT SECURITY WORK Shift left security sounds great in concept.

But, how well the development team embraces it will depend on the pipeline design. Do we design code build, scan, test and deploy into a single pipeline?

Definitely not – else every build will take hours if not days to run.

Developers are keen to find out if the code they build integrates well with the rest, and that needs to be done as often

as possible – preferably once a day based on a trunk approach. Therefore, breaking up build, scan, test and deploy into respective pipelines is the best way to allow developers flexibility to increase the velocity and efficiency of the DevOps process. Depending on how long scans or automated testing runs are, weekly or even longer batch jobs can be scheduled to accommodate that. Other determining factors include how fast codes are generated and how large the development is.

By now, it should be clear why adopting shift left security in code development is preferred – from more efficient software rollout to alleviating security domain issues. Moreover, commercial and open-source tools are readily available in the market to help us with its implementation. For your easy reference, I’ve listed examples in various categories in the box.

SECURITY AND CODE QUALITY TOOLS

For General Code Quality and Static Code Vulnerability Source code is examined to check for duplicate codes, complex ifelse while loops, its maintainability, the design of naming conventions, vulnerability to the OWASP and CWE threat list.

For Dynamic Vulnerability Scans Also referred to as black box scans done from outside in, the scan is performed on the runtime with deployed binaries. The tools will crawl through various application inputs and responses and try to expose vulnerabilities.

Recommended tools: Sonarqube, Fortify SCA, CheckMarx, Appknox, Snyk, and CodeScan.

Recommended tools: Fortify Webinspect, OWASP ZAP, Netsparker, Appscan, CheckMarx, and Acunex.

For Dependency Libraries Vulnerabilities Dependency open-source libraries used by DevOps applications can be vulnerable to security issues so scanning for OSS vulnerabilities is critical as they have a large attack surface and most organisations do not have a good system for vulnerability tracking and expedient updates. This scanning process, also known as software composition analysis, scans each OSS library.

Recommended tools: Nexus Lifecycle, OWASP Dependency Check, OSIndex, Snyk, and Gemnasium.

For Container Security Container security tools provide close signature monitoring of container drifts and rogue containers, scan for container setup errors and vulnerabilities, and provide risk scoring for each vulnerability by taking into account metrics such as whether the container has internet connection, open ports and attached security profiles. These tools also provide trusted image feature controls to check that specific image registries and even specific images are used.

Recommended tools: Aqua Security, Twistlock, Claire, Docker Bench, Anchore, and Trivy.

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THE BIG IDEA

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THE IT SOCIETY / Issue 02/2021

How AI is Disrupting the Retail Industry Disruption

EU KWANG CHIN Fellow, SCS IT Director, DFI Retail Group

CHERIE TEO Product Line Analyst, Data Lake & Analytics, DFI Retail Group

The world has changed since the first COVID case was reported in 2019. All businesses including the fast-moving consumer goods (FMCG) industry, despite being an essential business, are hugely impacted. Notably, some key challenges were also amplified – volatile stock levels resulting from panic buying compromise the accuracy of stock forecasts while border restrictions and lockdown measures disrupt production and timeliness of shipments. Question is, how can we leverage technology to overcome these challenges in a quick and effective manner?

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achine learning and Artificial Intelligence (AI) hold the answer to this question – use machine learning and AI algorithms to transform big data into smart data and infer from patterns to learn and adjust. This continuous and robust learning makes use of data to generate prescriptive actions that can be executed operationally while sustaining efficient and effective supply chain and store operations.

FROM BUILDING TRUST TO BUILDING PRODUCTIVITY In the context of the retail industry, earning customer trust through consistent delivery of great value and service is quintessential. Often, this means going back to the fundamentals of placing products customers want at the right place, right time and right price. However, existing systems and operational processes present multiple ordering and replenishment challenges that result in out-of-stock situations and untimely replenishments. These frustrate customers who made an effort to go to the stores (both online and offline) but cannot find the product they want – a pain point.

In a recent pilot implementation, DFI deployed machine learning capabilities to minimise out-of-stock situations without building excessive stockpile. Up-to-date and precise stock information is fed into the machine learning engine and aligned with existing operation rhythm before machine learning algorithms are used to predict optimal order quantity for each store. The projections are then sent to suppliers with delivery lead time built-in to ensure that stores receive the right order quantities on the right day, and in a sustainable manner. Significantly, the adjusting of existing operational

tempo to eliminate manual processes and streamline operational processes also led to increased productivity.

FROM IMPROVING EFFICIENCY TO IMPROVING SALES PERFORMANCE As proof of concept, the pilot implementation adopted a scientific approach to compare results between a test product group and a control product group. The products in both groups were identified on the basis that reliable performance comparison can be made between the current ordering process and the machine learning-based ordering process. Additionally, the machine learning ordering system went through four weeks of learning based on actual business data prior to comparison.

In the ensuing two weeks after learning, superior sales performances and reduction in shrinkage (write-offs) were observed in the machine learning ordering system. And even during a special event day (Halloween), the system was able to adjust automatically in response to increased demand – leading to higher sales performance.

This superior performance comes on the back of higher efficiency with less reliance on human interventions, as key data inputs are fed into the machine learning ordering system daily and each store’s optimal order quantity is sent to suppliers automatically. Several manual steps are eliminated.

Furthermore, in just four weeks of learning, the machine learning ordering system is already outperforming the existing ordering process. As the machine learning prediction becomes more accurate over time, the performance is expected to improve further.

SALES DOLLARS (PRE PILOT VERSUS PILOT)

9/16/20

9/26/20

THE BIG IDEA

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10/6/20 test skus

PILOT START

10/16/20 control skus

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FROM SHARPENING BUSINESS ADVANTAGE TO SHAPING BUSINESS SUSTAINABILITY By using available data, machine learning has provided better and new actionable insights to help retailers curate a superior and fresher product range, as well as achieve more competitive pricing and healthier stock levels. These data-driven capabilities coupled with changes to existing business processes enable retailers to sustain high performance in an increasingly competitive environment.

There are many use cases where retailers have benefitted from the deployment of machine learning capabilities. Besides leveraging advanced analytics like customer basket analysis to predict, upsell or cross-sell complementary products, promotions and offers can now be tailor-made according to customers’ purchase patterns. Strategic product placement can also be made based on customers’ propensity to purchase both products if they are within sight at the same time. Similarly, non-performing products can be replaced based on recommendations provided by such capabilities.

Most importantly, as customer purchase patterns continue to be captured, modelled and refined daily, not only can customers always get the products they want in the store they choose to go to, businesses are also assured of delivering good customer service every time. Undoubtedly, machine learning capabilities are key to ensuring sustainable business performance in the current COVID-shaped business landscape.

HALLOWEEN

10/26/20

11/5/20

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SPOTLIGHT

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THE IT SOCIETY / Issue 02/2021

RISE OF ARTIFICIAL INTELLIGENCE IN THE PANDEMIC:

Are You Ready to Take Advantage of It? LEE JOON SEONG Senior Member, SCS Member, SCS AI Ethics & Governance Certification Committee Managing Director and Applied Intelligence Lead for Southeast Asia, Accenture Age: 49 Earliest Tech Experience: Coding in C++ for a banking application Just Binged: Lupin Currently Reading: In Love with the World: A Monk’s Journey through the Bardos of Living and Dying by Yongey Mingyur Rinpoche and Helen Tworkov An App You Can’t Live Without: WhatsApp Last Surfed Topic: How to replace car valve cover gasket Latest Obsession: His classic car – 1976 Triumph Spitfire 1500 Favourite Way to Relax: Running, boating, and fiddling with his classic car

If businesses had previously believed that Artificial Intelligence (AI) could give their business a boost, the pandemic has confirmed this belief – by keeping supply chains undisrupted amidst changing border restrictions and productivity high even with remote work. But is there a catch underpinning the promise of these advantages?

Lee Joon Seong, Managing Director and Applied Intelligence Lead for SEA, Accenture weighs in on this during his recent chat with The IT Society.

Q: Question, JS: Joon Seong Q: More than ever, AI adoption has taken centre stage for businesses. Why do you think it is so?

JS: AI has been around for over two decades. However, it really took off in a big way over the last five years largely due to digitalisation, big data and cloud technology adoption globally. These trends have not only created an ideal environment for AI to grow exponentially, but also resulted in an evolution of AI’s role within organisations. In the early days, businesses relied on AI for simple tasks such as process automation. Today, AI plays a much more sophisticated role, augmenting decision-making processes and supporting data analysis across functions and industries.

AI is increasingly leveraged to tackle difficult challenges, transform operations and unlock new possibilities. More importantly, AI is table stakes for companies looking for competitive differentiation. Our recent research1 revealed that 84% of C-suite executives believe AI can help them achieve their business objectives. Another study2 showed that AI has become a high-stake business priority with a total investment spend of about US$300 billion in the last three years. We are also seeing companies that were able to scale AI successfully enjoying returns on investments of up to three times more3 than those unable to do so. These numbers make a strong case for AI and highlight just how big a role AI plays in businesses today and the years to come.

Q: What is the impact of the pandemic on AI deployment?

JS: The pandemic has undoubtedly forced companies to rethink their business models and accelerate digitalisation for survival.

But AI is one step above that – it gives companies an edge and helps them pull away from competition. Some examples include the use of AI in manufacturing for demand forecasting and workforce planning, and resource allocation in healthcare institutions. Notably, this process engenders a virtuous cycle where richer and more diverse data sets fuel the development of more accurate algorithms, which in turn empower greater speed and agility. The prediction is that digitallyenabled, AI-powered organisations will emerge as winners.

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That being said, we need to be cognisant of the fact that AI is not a silver bullet. Besides being clear about the benefits AI can deliver to their company and how it aligns with their business objectives, businesses must ensure that their people are able and willing to embrace changes brought about by the introduction of AI. Customer readiness and trust in the system are equally important.

Q: So has AI reached its full potential? Or what more can businesses do to benefit from AI adoption?

JS: AI adoption is still at a nascent stage and many companies face challenges in adopting it at scale.

One barrier companies often face is the lack of alignment between AI investments and corporate strategies. Without alignment, it is hard to be certain that investments are channelled to areas that will impact corporate objectives most positively. The best bet for any successful AI deployment is to have a C-suite champion who will shape and drive this alignment, and oversee the execution.

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Talent shortage is another obstacle. AI talent doesn’t only cover professionals with deep tech skills, but also “AI artists” who can translate a business problem into AI use cases.

It is no secret that good data is fundamental to AI development.

Implementing proper data governance – including managing customer data privacy, preferences and security – and building trust is essential for scaling AI. Additionally, a strong data and technology infrastructure is essential for supporting AI at scale – cloud solutions and modern data and AI architecture. Companies also need to have in place capabilities for AI practitioners to experiment, develop and deploy applications at scale.

Q: What do you see is the future of AI? How can tech professionals and businesses play a role?

JS: For AI to scale sustainably, it has to scale responsibly. Concerns around AI ethics and risks pose challenges for

SPOTLIGHT

businesses aspiring to scale their AI adoption. It is pivotal that AI ethics and governance are integral to AI development and not separate from it.

It is essential to have a transparent, explainable and accountable ethics and governance framework that provides clear guidelines on continuous impact assessment across different life cycles of the AI. This will be central to enabling an AI that is fair, unbiased and optimum.

For businesses, this highlights the importance of creating a robust data and AI governance framework. For tech professionals, education in arising AI ethics and governance issues on an ongoing basis is a must. I strongly believe that Singapore has a unique opportunity to position herself as the AI hub of the world and be a leader in framing and shaping the AI ethics and governance agenda for the future.

“Companies should evaluate their current AI capabilities against achieved business results, and relative to competition. This understanding of gaps and opportunities will help frame their AI strategy and determine investment priorities.”

What is a quote you live by?

What excites you about the AI scene?

I am looking forward to the day when…

What is an advice you have for aspiring tech professionals?

Did you know that SCS administers AI Ethics and Governance training and certification for professionals?

Check it out at www.scs.org.sg/courses-and-certifications https://www.accenture.com/us-en/insights/artificial-intelligence/ai-investments https://www.accenture.com/be-en/insights/applied-intelligence/professionalization-ai 3 https://www.accenture.com/us-en/insights/artificial-intelligence-summary-index 1 2

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THE IT SOCIETY / Issue 02/2021

TECHNOLOGY:

To Trust or Not To Trust?

PROF LIM SUN SUN Fellow, SCS SG100WIT List 2020 Professor of Communication & Technology and Head of Humanities, Arts & Social Sciences, Singapore University of Technology and Design (SUTD) Earliest Tech Experience: Bulletin board systems Just Binged: Chernobyl Currently Reading: New Laws of Robotics

by Frank Pasquale An App You Can’t Live Without: Duolingo Last Googled: How to convert cup measures to grams (for use in a pizza recipe) Pet Topic: Social inequality Favourite Way to Relax: Running, finding hacks to simplify complex recipes

According to the latest Edelman Trust Barometer, global trust in technology fell to an all-time low in 2021. As users grapple with the pandemic, they also struggle with issues like data privacy and misinformation – ills seen to be exacerbated by ever advancing technologies. Can this relationship be salvaged, or is there going to be an ever widening rift between us and tech?

SUTD Professor Lim Sun Sun shares her views with The IT Society.

Q: Question, SS: Sun Sun Q: What accounts for the falling levels of trust users have towards tech?

SS: In all systems – whether human or digital – we want to be assured that they are fair, ethical, transparent and reliable.

The way technology has been used in recent years have called these points into question. Take digital rights of children for example. When children interact with devices, companies can track their preferences and use that data to market to them. In this case, data is exploited against children who are too young to understand their rights as individuals – creating ethical issues.

There’s also the problem of a lopsided power asymmetry between technology companies and end users. As Artificial Intelligence (AI) and technology become more complex, end users find it challenging to understand what exactly goes into the decisions being made and how to make the right decisions when interacting with them. Yet, there’s little expectation on companies to be transparent. It is this lack of transparency that causes doubts to creep in and undermine the level of trust.

Q: How can we engender greater trust in AI and technology?

SS: We are beginning to see some tech companies taking positive actions

to make their terms of use and privacy policies more accessible. While that’s a small step in the right direction, I think regulators should intervene and clearly enunciate the expectation of transparency and ethics companies must be held to. For example, regulators can impose requirements to have inhouse ethicists, who not only know the principles of ethics, but also advise on translating these principles into practice.

This is where professional frameworks like the SCS AI Ethics and Governance Body of Knowledge also play an important role. Tangibly, the clear articulation of ethical guidelines and best practices helps companies improve

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processes and guide employees in prioritising these principles. But the symbolic value might be greater.

By capturing these principles in black and white, it signals to the rest of the world what the professional tech community stands for – which goes a long way in inspiring trust from various stakeholders.

Regulators will be more open to helping the industry achieve these standards, and consumers will have greater confidence that tech companies are taking ethics seriously. On the global scale, this reassures investors and talent that we have done our due diligence.

Q: Would this be enough to keep everything in check?

SS: In reality, technological systems are so deeply embedded in our everyday lives that it cannot be the purview of a single

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party. It shouldn’t just be companies, regulators or end users alone. Ideally, it would be a dynamic relationship between the different stakeholders – where each party balances and keeps the others in check.

But beyond professional frameworks and standards of transparency, we also need to think about fixing the system upstream. Technology designers should be educated on ethical principles from the get-go, especially since there is usually no one perfect choice. By schooling technologists in ethical principles, they become better equipped to make judgement calls when deciding between trade-offs. This is also where in-house ethicists can provide advice specific to the situation – whether it’s designing video sharing platforms or surveillance systems. This would help ensure that the code written and systems created are transparent and ethical – in accordance with our values and moral standards.

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Q: Moving forward, what’s in the cards for our relationship with technology?

SS: We are pretty much moving into uncharted territory. The roadmap we followed in the early days of tech doesn’t work anymore. So in a way, we are at an inflection point to reconsider the big questions about ethical and societal issues we talked about earlier. How do we make technology more humancentric? Or how can we undo the wrongs done? Can we reinvent aspects that have become entrenched? And so on.

At the same time, even as we adapt to technology, technology is also being reshaped according to our lifestyles and practices. This mutually influential relationship will most likely change the outcomes and consequences of issues we face today. Along the way, we will also get a better sense of how we want technology to work for us, and in our best interest. Essentially, it’s going to be an evolving conversation.

“One of the greatest fears people have towards technology is being displaced by automation. But if there’s one thing the pandemic taught us, it’s that we crave human connection more than we realise. For aspects of our lives like education and healthcare, there’s always going to be a point where society decides that this will be our limit for automation – and that’s enough.”

WHAT CAN WE EXPECT FROM A TRUSTFUL DIGITAL ECOSYSTEM?

BETTER products and services.

Businesses gain access to more accurate and comprehensive data sets – as users feel more comfortable sharing data.

BETTER solutions to complex digital problems.

A mature trust ecosystem involves a large and diverse group of stakeholders – bringing about greater cooperation and ideas.

BETTER interconnectedness.

BETTER digital sustainability.

The element of trust enhances the quality of digital connections – whether person-to-person, person-to-machine.

Digital trust forms the basis of a sustainable digital ecosystem – one that balances wide-ranging concerns (e.g. social, environmental, economical).

Source: Deloitte, Future of Digital Trust: Driving forces, trends and their implications on our digital tomorrow, https://www2.deloitte.com/content/dam/Deloitte/de/Documents/ risk/Deloitte-Future-of-Digital-Trust.pdf (2021)

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POWER BOOST

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Should Trust Come Before Tech or Tech Before Trust?

THE IT SOCIETY / Issue 02/2021

As Singapore invests $50 million over the next five years to build our digital trust capabilities, we bring you up to speed on why digital trust matters and how businesses can lose trust – irrevocably.

WHY DOES DIGITAL TRUST MATTER?

58%

are unlikely to purchase from a business they distrust.

71%

of Asian consumers reported being more cautious about providing personal information online – potentially putting the brakes on data-intensive technologies.

Digital trust stands to be a

competitive differentiator in the age of Big Data and Internet of Things.

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POWER BOOST

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HOW CAN BUSINESSES BUILD DIGITAL TRUST?

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4

Transparency and accessibility

Ethics and responsibility

Privacy and control

Security and reliability

• Adopt tools that ensure fairness and detect biases

• Give customers greater control over data sharing

• Implement safeguards against unethical/inappropriate use of technology

• Limit data collection/ analysis to necessary data

• Be proactive in notifying customers about suspicious activity

• Be transparent on how data is stored and used • Offer easy-to-understand disclosures (e.g. privacy policy, terms of use)

• Reduce errors/fraud with AI and automation

WHAT CAUSES BUSINESSES TO LOSE TRUST?

50%

of Asian respondents lost faith in a company due to a data breach/security event.

45%

of Singaporeans stopped using a company’s services permanently after data misuse/breach.

Singaporeans’ top reasons for distrust include:

intentional misuse/selling of data (38%) data breaches (19%) changing of terms without notification (16%)

Sources: Accenture, Trust in the Digital Age, https://www.accenture.com/_acnmedia/pdf-47/accenture-trust-digital-age.pdf (2017) Deloitte, Building Digital Trust: Technology can Lead the Way, https://www2.deloitte.com/content/dam/insights/us/articles/6320_Building-digital-trust/DI_Building-digitaltrust.pdf (2019) Okta, The State of Digital Trust, https://www.okta.com/sites/default/files/2021-05/ASIA_DigitalTrustReport.pdf (2021)

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POWER BOOST

15

Human-Computer Relationships: Should Trust Be Given or Earned?

For as long as computers existed, applying them in any practical way required some technical skills.

Training is often required even for simple applications like Word and Excel. But what if you could simply tell the computer what you need, and your electronic companion would do the rest?

I

• A songwriter uploads a chord n fact, the recent wave of AI is progression to a musical algorithm doing exactly that. It is capable of which arranges the tune in seconds. interpreting natural human expression The songwriter tweaks the melody as well as translating it into code and further. After some improvisation back. Will this development change the with the computer, a song which importance of creative skills vis-à-vis could easily blend into many Spotify programming? And can we trust a playlists is recorded. computer with so much creative power and agency?

• A painter doodles a sketch and lets the algorithm extrapolate it into a SYNERGY HAPPENS WHEN complete painting. He adds more THERE’S TRUST details to refine the artwork. He can While solutions such as no-code visual also ask the machine to animate the programming made building new drawing and turn it into a cartoon, if software simpler, some amount of he wants. technical savvy was still required. New algorithms however, which can translate natural expression into code, have changed the playing field in a more profound way. Here are some examples: • A designer outlines a video game in simple English in a text editor – or verbally (since the AI engine can recognise speech). The AI engine translates that into code.

Soon, a game similar to Space Invaders emerges as the designer continues to describe the playing rules.

VLADYSLAV KOSHELYEV Member, SCS Academy Lead, Facebook Founder, The Koshelyev Company

TRUST BRINGS OUT LATENT POTENTIAL Look at these scenarios as the start of a sharply accelerating trend, and it becomes hard not to be excited about the power AI puts in the hands of creators, entrepreneurs and visionaries. As this technology matures, writers and designers, painters and musicians, philosophers and lawyers will foreseeably become as important as the engineers who build these tools.

LACK OF TRUST SEEDS DOUBTS Over time, we can expect the AI to increasingly interpret ideas at a higher level of abstraction, and offer innovative solutions and tools – even beyond human comprehension. Trust becomes a paramount concern against this backdrop. Is the app built by your AI free from backdoors? Is the strategy designed by the algorithmic analyst really good for your organisation in the long run? How about the software that built that app, which coincidentally was also developed by an AI? ONLY HUMANS CAN GIVE TRUST It is fair to say that we do not have all the answers. Perhaps, we will keep humans in the loop for as long as we can. Possibly, we will use AI auditors to check their developer counterparts for irregularities. Regardless of the future solutions, it is clear that for this new generation of tools to reach its potential, we will need to trust them in the same way we trust any other complex technology – such as the bridge will not fall when we cross it, or the car will stop when we step on the brakes.

We are entering the age of human-computer interaction – and trust is the fundamental human quality that will determine its course.

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17

AI Ethics and Governance Body of Knowledge Turns One

T

o support AI development, the AI Ethics and Governance Body of Knowledge (BoK) was first launched in October 2020 – offering a set of guidelines with fairness, explainability and transparency forming the core, standard set of ethical values.

building user trust in AI to foster an environment where businesses and consumers feel safe and confident about using digital technologies.

With AI increasingly deployed across sectors such as healthcare, legal, and manufacturing, building a safe and fair

Almost a year on, the BoK’s significance has grown. In July, Minister for Communications and Information Mrs Josephine Teo spoke at the ATxAI Conference about the importance of

AI-enabled environment has become especially critical. The BoK therefore serves to address the gap between AI researchers and experts who develop state-of-the-art AI technologies, and the diverse stakeholders who operate, interact with, and are otherwise impacted by these technologies.

In celebration of the AI Ethics and Governance BoK’s 1st anniversary, SCS is extending complimentary access to all SCS members! Get your digital copy (worth $30) at https://ai-ethics-bok.scs.org.sg

AI ETHICS AND GOVERNANCE IN ACTION Organisations Pledge Support for AI Ethics and Governance

SCS-NTU AI Ethics and Governance Certification Course

In tandem with the AI Ethics movement, organisations from various sectors of the industry have been encouraged to pledge their commitment to:

Launched jointly in April 2021 by Singapore Computer Society and Nanyang Technological University, this certification course is designed to help professionals acquire knowledge in applying ethical AI practices in organisations as well as understand and help societies solve problems brought about by the impact of AI.

• Become more aware of ethical issues in the development and deployment of AI solutions • Share understanding, knowledge and awareness of the need for ethics with colleagues • Participate in AI Ethics and Governance training and certification programmes

To understand more about the AI Ethics and Governance pledge or pledge on behalf of your organisation, please email rachel.seetho@scs.org.sg

The certification course will examine candidates’ competence in five areas of AI Ethics and Governance: • • • • •

Body of Knowledge (BoK) for AI Ethics and Governance AI Ethics Governance Framework for Organisations Ethics in Data Processing Business Liability and Ethics in AI Usage Governance for AI Explainability Sign up for the October intake at www.scs.org.sg/certifications/ application

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18

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THE IT SOCIETY / Issue 02/2021

Keen to Help Proliferate AI Ethics and Governance in Your Organisation?

A

precursor to the BoK, the AI Ethics and Governance Toolkit provides an overview of AI governance issues and explores a risk-based approach to deploying AI. The Toolkit is useful for both tech and non-tech professionals to understand ethical issues surrounding AI.

THE AI ETHICS AND GOVERNANCE TOOLKIT: AN OVERVIEW AI Ethics and Governance is important because…

AI can cause harm if improperly configured.

AI can be used to aid responsible decision-making.

AI must be deployed responsibly to inspire trust.

AI Ethics and Governance is everyone’s responsibility because…

During development, developers/data scientists are focused on product functionality rather than ethical considerations.

Without accountability/formal compliance requirements, the product might fall short of customer expectations.

Improper AI deployment can cause legal/ reputational risk and loss of public trust.

The broader team (e.g. business leaders, risk managers, IT or HR staff) can provide greater oversight.

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4 PRINCIPLES OF AI ETHICS AND GOVERNANCE PRINCIPLE

PRINCIPLE

01

02

Human-Centric

Transparency

Case Study: Ngee Ann Polytechnic

Case Study: UCARE.AI

NP hired EVA, a virtual assistant, to automate the review of application essays – shortening time taken from 470 hours to two. This freed employees to do higher value tasks.

UCARE.AI, a Singapore-based startup, offers AIpowered cost predictor services to hospitals.

However, EVA did not completely replace the process. NP also implemented internal governance structures and measures to ensure oversight.

To build trust and confidence, UCARE.AI discloses the parameters in developing the AI to clients, as well as offers explanations for algorithms that affect operations, revenue or customer base.

PRINCIPLE

PRINCIPLE

03

04

Fairness

Explainable

Case Study: LinkedIn

Case Study: Visa Asia Pacific

LinkedIn’s recruitment tool sets the premise that gender does not impact candidate suitability.

Visa offers Travel Predict, a machine learning product that predicts cardholders’ future travel behaviour.

To prevent discrimination, qualified candidates are first divided by gender. Each group is then staggered before being combined (e.g. top five women and top five men) to show a balanced mix.

Predictions are explainable as Visa shares top predictor scores and key performance indicators on prediction and accuracy with issuing banks.

Download the AI Ethics and Governance Toolkit at www.scs.org.sg/ai-ethics-bok

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Nominate the Next Tech Leader!

T

echnology, especially in vaccines and digitalisation, has and will continue to have a profound impact on many facets of our lives.

The rapid and wide adoption of digital technologies in our society today calls for a transformation of our IT Leader Awards to be more inclusive. That is why SCS has rebranded this acclaimed award to Tech Leader Awards.

21

KHOONG HOCK YUN Fellow, SCS Member, SCS Executive Council Chairman, IT Leader Awards Committee

Tech Leader Awards aims to recognise individuals and teams who have contributed to the digital transformation of our society – regardless of whether they are digital professionals in the ICT industry or adopters of digital technologies in economic and non-economic sectors; young or old; and in the past, present or future.

Specifically, SCS seeks to celebrate and recognise outstanding individuals and teams whose work in Digitalisation and Transformation have positively impacted our lives at Tech Leader Awards 2022. Through this recognition, SCS looks to inspire and spur others to likewise innovate, persevere and deliver sustainable beneficial outcomes to society and industries – building a stronger, more competitive and connected nation as we emerge from the COVID-19 pandemic.

TECH LEADER AWARDS 2022 CATEGORIES

TECH LEADER OF THE YEAR nominees should have led digital technology innovations or breakthroughs which benefitted the infocomm and digital media industry, and a track record of outstanding contributions to the infocomm and digital media industry beyond personal and immediate business interests.

HALL OF FAME nominees should have helped shape the sustainable development of infocomm and digital media in Singapore over an extended period of time.

DIGITAL ACHIEVERS nominees should have implemented digital infrastructure, platforms or applications that benefitted multiple companies or organisations by enabling a significant breakthrough in business and/or society product and/or service delivery.

Alternatively, nominees had led in innovations and inspiring digital transformation work that significantly benefits industry/society.

FUTURE LEADERS IN TECH nominees should be aged 30 years and below (as of 1 January 2022), made outstanding personal contribution to the industry/ society while being a full-time student in Singapore schools or institutes of higher learning. They should also have instilled passion for infocomm and digital media among their peers.

Candidates in all award categories should possess qualities such as integrity, exemplary leadership, entrepreneurship, perseverance, and competence in the development/use of digital technology in their work.

Nominations are open now till 31 October 2021. For more details, please visit www.scs.org.sg/awards/tech-leader-awards/2022/nomination

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GEEK SPEAK

25

Frankly Speaking: Are We Trusting Too Much?

H

ello everybody, I’m Frankie – remember me? I used to write this column, sharing my daily adventures (and misadventures of tech) before going into “retirement”.

It is said that a certain prominent Malaysian politician did what most of us didn’t: reply the email. In the end?

He became US$650 million richer! So who’s the smart one?

Fast forward – the editor invited me to share funny stories about “Trust”. I thought since he trusts me, I shall not disappoint him. Hmm.

DO YOU TRUST YOUR GPS? Most drivers today no longer keep the trusty Mighty Street Directory in our cars or depend on it to take us places. Instead, we simply key the destination address or postal code into the GPS. For the more advanced ones, it’ll just be “Hey Siri, take me to…“

It is said that we don’t trust people for two reasons: first, we don’t know them; and second, we know them. I think this applies to computers and machines too!

FREE MONEY FROM NIGERIA (OR UK OR VENEZUELA)?

Ever received emails claiming that someone has left you a fortune? Confirm that you’re the deceased’s relative, and half the fortune is yours – for a few percent of admin charge. What did you do? Laughed and immediately sent it to the trash/spam folder?

Aren’t we smart? But what if it’s real – and the fortune really exists? Well, we’ll never know.

And what do we do when we know we should drive straight but the GPS says “Turn right”? We (me included!) follow the GPS instructions – even if doubtful. I did that before; and will likely do it again. But I hope I’ll never have to decide to turn right to the side road – or drive straight (as the GPS commanded) into the river. (www.youtube.com/ watch?v=QcrRvQny7mM)

TO VAX OR NOT TO VAX: THAT SHOULD NEVER BE THE QUESTION! Yet, through the wonders of unregulated social media posts and ubiquitous chat group sharing, many had “researched” and “followed” articles and “news” which prove that vaccination is a conspiracy to inject poison into us, with a yet-to-be-determined agenda. Then, as if by coincidence, search engine algorithms also circulate news that perpetuate our beliefs. Such is the power of tech – reinforce what we believe in. Scary.

As far as Frankie is concerned, I have concluded (in my mind) that all of us will somehow, somewhere in the future be infected by COVID-19, COVID-21 or COVID-2x. But Frankie is not only fully vaxxed, but also enjoying benefits of dining in at food courts and restaurants, watching movies, and so many other things! Join Frankie to do what you believe is right – before it’s too late.

WHAT ABOUT FACEBOOK? Hmm. Tricky. So please allow Frankie to say: It’s at another level!

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