Sync NI Magazine Autumn / Big Data 2023

www.syncni.com Autumn 2023 eir evo PA Consulting Aflac

magazine

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Harnessing the power of Big Data Analytics Engines

12 Q&A with EY’s Gareth Kelly

18 Welcoming

Kainos’ new CEO

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Welcome to the autumn edition of Sync NI magazine Foreword

Dr Scott Fischaber

Co-founder and COO at Analytics Engines

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t has been quite the year for data, with artificial intelligence seemingly going from science fiction into the public headlines overnight. Governments across the world are now seeking to understand how they can (and should) provide regulation and guidance in this field to ensure public safety and trust. I recently had the opportunity to meet with the Chair of Responsible AI UK, Professor Sarvapali (Gopal) Ramchurn, and gather with fellow peers from across industry and academia at the Responsible AI Town Hall, where we discussed major challenges of building, deploying, and regulating AI so that it is safely and responsibly used.

The concept of an 'ecosystem' was a key term that came up and is also in the UK government's AI strategy. An ecosystem is a web of interactions within a specific setting, encompassing all sorts of relationships and transactions.

Currently, the realm of ethical AI is disjointed. The mission of Responsible AI UK is to consolidate existing programs while collaboratively forging new paths.

The approach isn't to build this network from scratch; rather, it aims to connect and enhance current efforts, serving as a catalyst for collaboration among existing entities and initiatives.

We should take a lesson from this approach; our region is known globally for the abundant talent and skills our population base has in the tech sector, particularly in AI and data analytics. We have several major clusters of excellence in AI research including cyber security, hardware, IoT, medicine, robotics, multi-

media, analytics and economics. With additional funding into this sector coming through the City Deals, this is only likely to accelerate the growth of knowledge and the skill base in this sector, but as a region we need to ensure that this operates as an ecosystem, not as disjointed projects.

If we can successfully create this web of interactions across the AI and data analytics initiatives throughout the region, taking advantage of the unique expertise of each, we have a fantastic opportunity to have a world leading ecosystem for data and AI work across industry, academia, and research organisations. There’s an added benefit for our local companies as well, taking advantage of this local expertise to apply to our businesses across the region.

We have a unique opportunity here to ‘have our cake and eat it too’.

At Big Data Belfast on 26th October, we will bring together leaders in our industry to hear and discuss how they have used data to drive growth within their businesses. Not only is this a chance to gain insights into the business value that data and analytics can have for organisations, but we also get the opportunity to come together as an industry and, at least informally, create the interactions necessary for a healthy ecosystem. Generative AI as a topic will form a dominant part of the day, where our speakers will take the chance to go beyond the media hype and look at how this technology can be used to solve real-world problems alongside the legal, ethical and regulatory challenges that go along with this. The technological landscape changes year-on-year, but the challenges and opportunities largely remain the same.

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About Sync NI Sync NI is proud to be the voice of Northern Ireland’s vibrant technology and business sector.

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No responsibility for loss or distress associated to any person acting or refraining from acting as a result of the material in this magazine can be accepted by the authors, contributors, editors or publishers. Sync NI does not endorse any goods or services advertised, nor any claims or representations made in any advertisement in this magazine.

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Inside this edition 06 Big Data Belfast returns with amazing speakers and thought-provoking topics

16 The rise of data and AI at Kainos 18 Welcoming Kainos’ new CEO

07 A catalyst for progress and the subject of ethical debate

20 Defining ICT infrastructure for big data success

08 Big Data Belfast 2023

24 Don’t overlook the data behind comms

09 AI gives players the competitive edge, both on and off the pitch

26 Danske Bank: Data-enabled digital transformation 28 Data literacy: Why it matters for your business

10 What does the future hold for Data Scientists?

30 “Shaping” the 4th Industrial Revolution with CGI

12 Q&A with EY’s Gareth Kelly

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32 Northern Ireland to North America: The Belfast data company transforming healthcare 34 How data plays a role in Fintech

40 The Annual Dell Technologies Forum 2023 42 PA Consulting announce investment in new roles 44 Changing the world with future-driven Fintech

36 Big data, big opportunity, big challenge

46 Q&A with Keith Farley

38 Large language models (LLMs) in big data: Democratising access to data, or a new wild west?

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49 Helping AI help us meet today’s biggest challenges

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Big Data Belfast returns with amazing speakers and thought-provoking topics Dr Aislinn Rice, Managing Director at Analytics Engines introduces this year’s Big Data Belfast conference

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am delighted to take the opportunity to introduce some key announcements in the lead-up to this year’s Big Data Belfast 2023 Conference, curated and organised by Analytics Engines.

AI solutions for many years. Since the release of ChatGPT, there has been a significant step change in the capabilities of LLMs and we have been deeply immersed in the new ecosystem of tools and techniques.

Analytics Engines now act as a solutions advisor and implementation partner to unlock business value with LLMs and AI.

Every year, we present international speakers and current topics to a thriving tech community here on the island of Ireland. It’s a chance for delegates to learn from their peers, elevate their thinking and be inspired by leaders who take to the stage.

From the wealth of experience in the room, both on stage and off, it is clear that we have a vibrant and ambitious tech community who thrive on collaboration and innovation. It’s no surprise that Northern Ireland is now being referred to as a ‘testing centre’ for Artificial Intelligence in the UK. Analytics Engines are at the forefront of innovation in the field of AI and we hope to inspire conference delegates with some of our own exciting developments and customer stories.

This year we want to shake out the important topics that matter to everyone regardless of their professional pursuit. It’s no

Dr Aislinn Rice

surprise that climate, ESG and net-zero objectives are at the forefront of many organizations as they journey on their way towards their sustainability goals.

Emerging technologies and innovation are the vehicle to getting us there with AI and data analytics having a central part to play in this.

technological innovation is to revolutionise the way businesses harness the power of data, enabling them to uncover the true narrative hidden within their information. Our core expertise lies in AI-enhanced search and discovery, propelling us to the forefront of cuttingedge solutions.

At Analytics Engines, our vision for AI and

We have been developing and implementing

Our mission is to facilitate intelligent decision-making by providing connected insights and fostering a deeper understanding of complex information on a significant scale. We envision a future where AI serves as an invaluable ally, assisting businesses in extracting meaningful patterns, trends, and correlations from vast and diverse datasets. That future is here and now; it’s in the data stories that businesses tell every year at Big Data Belfast.

Big Data Belfast serves as a national technology checkpoint. We know the ecosystem is thriving with innovation but sometimes it takes a gathering of minds to remind us that we have something special in Northern Ireland. So, mark the date as your annual technological and intellectual renewal- See you there!

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A catalyst for progress and the subject of ethical debate Stuart Gunning, Strategic Account Director discusses AI's dual role

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n the ever-evolving digital age, Artificial Intelligence (AI) has rapidly transformed from a lofty theoretical construct into an omnipresent force, with projections indicating that the AI market could burgeon to $190.61 billion by 2025.

Such staggering growth instigates an intriguing, sometimes divisive question: Is AI fundamentally an agent for positive transformation, or does it create a quagmire of ethical concerns?

For instance, let's consider AI's impact on the manufacturing sector, a cornerstone of the UK economy.

Advanced robotics and machine learning algorithms have drastically improved the efficiency and quality of British-made products. AI-powered predictive maintenance systems can now anticipate machinery faults before they occur, reducing downtime and saving millions of pounds annually for UK manufacturers. This operational excellence, however, isn't confined to factory floors; it extends to supply chain optimisation and even personalised marketing, drastically transforming how manufacturers interact with consumers.

Similarly transformative is AI's imprint on British business. Chatbots are offering around-the-clock customer support on retail websites, while fintech startups in London are democratising investment opportunities. Astonishingly, 76% of UK consumers now trust AI for financial advice, indicative of a profound shift in public sentiment.

However, the potential of AI isn't without its complexities. McKinsey estimates that AI could add an extra $13 trillion to the global economy by 2030 but also cautions that up to 800 million jobs could be automated.

Yet, the rise of AI is simultaneously spawning new employment sectors within the UK, especially in the realms of AI ethics, system maintenance, and data governance.

Transitioning to the subject of ethics, AI algorithms can perpetuate societal biases, particularly visible in sectors like predictive policing or employment screening processes. This issue is especially poignant in the UK, where a balanced approach to AI governance is being hotly debated. In such a nuanced ethical landscape, the need for transparency and oversight cannot be overstated; these are prerequisites, not

optional extras.

The issue of privacy remains a significant concern, with 63% of Britons expressing worries about how organisations handle their data, according to the UK Information Commissioner’s Office. As AI systems continue to refine their data analytics capabilities, finding an equilibrium between the utility of data-driven insights and the sanctity of individual privacy is an evolving challenge that society must address.

Conclusively, the multifaceted nature of AI—its undeniable benefits and its ethical conundrums—leads me to a stance of cautious optimism. Despite the challenges, AI’s vast contributions to sectors like manufacturing and finance offer more than a glimmer of positive impact. With concerted efforts to address ethical and privacy concerns, there's every reason to believe we can steer towards a future where AI amplifies both economic growth and social well-being. As we navigate this AI-imbued age, the collective goal should be to utilise this groundbreaking technology with efficacy and ethical integrity, maximising its advantages for the benefit of society at large.

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Big Data Belfast 2023 The Big Data Belfast conference returns to the ICC on Thursday October 26th for another full-day packed agenda covering all things AI & data

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ow in its 9th year, the conference is supported by headline sponsor EY. Other sponsors include Allstate, Aflac, Liberty IT, MCS Group, Wolfspeed, DELL, Insider Inc and Sync NI. This year’s speaker lineup will include household names like Minecraft, Jaguar Racing, Dr Norah Patten, Citizen Scientist-Astronaut Candidate as well as speakers from some of the big tech giants like Microsoft and IBM, with lots more to be announced over the coming weeks.

This year the event will aim to showcase and unravel the most relevant data and AI topics across various sectors including Sustainability, Transport, Media, Government, Technology and many others.

organisations and individuals to connect with; and to learn from innovative business leaders from the technology sector and beyond.

Attendees will discover how market leading organisations are using data to innovate.

The event will host multiple relevant themes, with a focus on using data and AI to solve some of the most challenging business, social, economic and environmental issues.

Patricia Spence, Head of Commercial Marketing and Big Data Belfast Lead said, “Big Data Belfast offers something for everyone in the tech community. We try to create something that peaks the interests of both the techies and the executives in the room. We

Big Data Belfast 2023 will be the ideal opportunity for

want delegates to leave feeling inspired with a new wealth of knowledge to take back to their day-to-day jobs. The hope is always that the impact of the event lives on beyond the conference itself.”

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AI gives players the competitive edge, both on and off the pitch To survive and grow in an increasingly competitive world, sports organisations need to reinvent themselves. Digital transformation programs and solutions powered by Artificial Intelligence will be a key differentiator to compete on and off the pitch, while increasing reach, acquisition, loyalty, and sales, inside and outside the venue

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ebastián Lancestremère, Sports Managing Director at Microsoft Corporation will be speaking at the upcoming flagship data and AI event, Big Data Belfast on Thursday, 26th October.

waste, water and energy consumption.

The utilisation of AI and wearables also has a huge impact on sport itself, providing coaches and athletes with realtime insights about game strategy, body movements, techniques, psychological analysis, and injury prevention.

Sebastian leads the Microsoft Sports practice, helping clubs, leagues and federations to become digital and sustainable businesses that completely reimagine the fan experience and discover new monetisation models.

Sebastián Lancestremère

According to Lancestremère, “The future of sports technology is incredibly exciting thanks to the use of data-driven insights and the growing potential of Generative AI. At Microsoft, our vision is to support the sports industry’s evolution into a “Sportainment” and “Datatainment” industry, with organisations transforming into media houses and data organisations.

work in this space to date hints at a future where the convergence of traditional industries through digital transformation is expanding into sports technology and the business of sports.

Generative AI is a ‘once-ina-generation’ technology that will enable us all to better serve the fan and create new experiences – which, as always, remains the touchstone of the industry.”

“This transition will create richer, more personalised content, products, and services, boosting current revenue streams, and creating new ones. Our

Similarly, to how AI in retail analyses consumer behavior to personalise recommendations and optimise the customer journey, AI in sports offers

tailored content and enhances fan interaction, thereby providing sports devotees with a more enriched and customised experience.

Beyond the fan experience, the integration of smart and cognitive technology into sports venues will also be transformational - not only in driving efficiencies but in aligning with sustainability commitments.

Technologies such as, Domotics, AI, and IoT can converge to support crowd management, security threat detection, and building management, all helping to minimise

Ahead of the event, Lancestremère highlighted the importance of opportunities to collaborate with a cross-section of industry leaders to discuss the transformative impact that AI can bring to different businesses. He continued: “It is vital we are coming together in Belfast to learn from perspectives and experiences and to discuss the potential opportunity that AI can bring to the business community here in this market. We are at the formative stages of this new era of AI so it’s great to see our partner, Analytics Engines bringing together, and showcasing how, market-leading organisations are using data and AI to innovate, ultimately creating better products, services, and experiences for their customers.”

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Marianna Imprialou, Director of Data and Analytics at EY, explores how the data science sector is set to shape different parts of our society q How has the Data Science sector been impacted by the advent of GenAI?

I would say that right now the day-to-day life of a data scientist has not yet been greatly impacted by the ‘Big Bang’ event that is GenAI however we can see and predict that changes are coming, specifically as the technology becomes more widely available offering the potential to streamline certain processes.

Data scientists working mainly with textual data have certainly started extracting insights in a much easier and more comprehensive way already. The rest of us have benefited mainly from the ability to write code faster but we are still at an early stage and are yet to see exactly what those changes will look like in the future. Currently, there is a lot of training going on in this area and people are certainly keen to embed GenAI in their work.

q What Gen AI applications excite you most in terms of transforming society?

Applications that are related to knowledge sharing and digesting excite me the most. Of course, there are numerous commercial applications that can lead to commercial gains which are exciting however for me I think back to my past in academic research. In the past, the number of books, papers or other resources someone could read to conduct a literature review for example was limited. In the future, the sheer volume of that information will change, and people will have access to an amazingly huge knowledge base. In that regard, when it comes to the important aspects of society and science, there can be no excuses for not being more informed about specific topics. Obviously, this has its own dangers as information must be checked, verified and be accurate but I think and hope that this will be achieved over time.

q As demand for Data scientists increases how can we

best develop these skills for the future?

Data scientists have always needed to be very good problem solvers, flexible thinkers and be able to adapt to any type of commonly used tool. Even before data science was even called data science people performing the data analysis work have always been quick to adapt, learn and problem-solve and that will never change.

Beyond these core skills and in a more practical sense I think that data scientists today should begin to focus their training on all these new GenAI tools and learn how to use them to their benefit. This means adopting the technology to enable

What does future hold Data Scient

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them to do more efficient work and complete more meaningful tasks at speed.

The next generation of data scientists will therefore need to adapt to a large variety of tools and software and focus on having a good knowledge of more than one programming language, database querying as well as multiple cloud infrastructures in order to remain flexible and versatile in their roles.

q As Assistant professor

at a leading UK university, how easy was it to transition from academia to industry?

the d for tists?

Marianna Imprialou

For people who specifically wish to transition from academia to industry wanting to follow a data science path it’s more straightforward than in other sectors. While aspects of my role as Assistant Professor involved teaching Data Science and Statistical methods a larger part of my time was involved in managing my own research projects as well as managing people who were working on data science research projects. This part of my previous role was not dissimilar to a principal data scientist role in a team within the industry and I personally found the transition quite easy.

Typically, when a data scientist moves from academia to industry many will already have been exposed to and experienced a large and wide spectrum of technologies, methodologies, statistical

models and algorithms across various sectors.

Academia helps to develop technical skills and provides access to many tools aiding the transition into industry.

For those who have spent a long time working in academia, the transition can sometimes be a bit of a shock in terms of how fast things move in the industry however the satisfaction that you get from the realworld application of what you do is something that is extremely motivating and to be honest, kept me going even at the most difficult of times at the very start of my career within industry.

q In what is often perceived as a maledominated industry, from the perspective of a woman and a mother, what has been your personal experience?

In a male-dominated sector like data in both academia and consultancy I can't say that there haven't been moments that I sensed, without having any proof of that, that because of my gender and sometimes even my age and gender in combination, certain people initially doubted or questioned my ability to perform specific tasks.

Even today in a team when someone meets me, they might assume that from a technical perspective, I might be doing the ‘lighter’ tasks on a project. They might think that the person who is writing the code is not me and I’m simply managing it and that really isn’t the case.

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In many ways, women do sometimes have to wait a bit longer and must prove themselves a bit more in the job to be trusted by our teams and our clients. I see this as a common theme and I’m not the only person to have experienced this.

Equally, I have to say that I have always found a lot of support from colleagues, male and female, and typically this does not become a persistent problem.

When I was younger, I did not think too much about this and took my position within the sector for granted however as a mother of a young girl my perception on the subject has certainly changed.

Ideally, I wouldn’t want this to be the experience for my daughter 20 years down the line and I feel it is my and our generation’s responsibility to erase this belief that women are less likely to be good at Maths, Physics or Coding. I think we need to encourage more girls to cultivate these skills but also to go into the workplace without feeling that they have to prove themselves more than others in order to succeed.

Today there are a lot of workplace initiatives, and many companies address this area in a positive way, so we are going in the right direction. For me personally, I feel a responsibility to work harder on encouraging others to feel more included, more so than I did at the beginning of my career.

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Q&A with EY’s Gareth Kelly As Partner in the Data & Analytics practice at EY Ireland, Gareth explains AI’s potential for many markets and how businesses will need to act to keep up with the everchanging tech

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q Big Data Belfast has established itself as one of the most important and prestigious events in the NI tech calendar – what makes it so attractive to you?

Big Data Belfast epitomises the very best of Northern Ireland showcasing leading technology, data and analytics companies. This event provides an ideal opportunity for delegates to gain valuable insights from an impressive lineup of international speakers and the best minds from across the globe. By having that perfect mix of tech, data and AI the event has proven to be incredibly successful as evidenced by growing consistently over the past 5+ years.

Being part of this event is so important for us at EY and truly aligns with the EY principles of working locally, but thinking and leading globally. For me, being part of this event celebrates the great talent we have in NI, our entrepreneurial spirit and the opportunity our region has to be a global player in data, analytics and tech.

As we embark on our journey towards 1000 new jobs in NI, Big data Belfast 2023 is a key milestone reminding us of the opportunity we have and the people that make living and working in NI so brilliant.

q Data Analytics has been a central function of businesses for decades – what are the most impactful features of AI in the current landscape?

I think the market is reacting in 2 ways to AI : some with excitement around the possibilities and others with a degree of trepidation. From our recent CIO survey (1200 CEOs in July 2023) 65% of CEOs recognise the potential for AI to drive productivity and positive outcomes for all stakeholders while, equally, 65% felt that there is more work required to address the social , ethical and criminal risks.

I actually lean towards the less doomsday view and remain very much excited by what AI is going to do – I think AI will greatly improve our working world and generative AI has the potential to be completely transformational. Generative AI is helping us to process and consume huge amounts of data, getting to insights faster, leading to better decisions and improved business outcomes. The ability to query, interrogate and ask questions of huge amounts of data and information at scale with an AI interface is incredible. The access to information and the speed at which we can curate that information is truly a revolution

q What are the current legal and compliance implications associated with generative AI?

The AI act is coming down the line and the EU aims to create a gold standard for the regulation of AI. This includes codes of conduct to encourage providers of AI systems to put in place appropriate controls and

safeguards for enhanced transparency around areas such as deep fakes, foundation models and high risk AI systems. High risk AI systems may exist in the likes medical devices, machinery, cars and even toys!

We can see this resulting in requirements for enhanced risk management processes, better data governance, technical documentation, robust cyber security, and ethical considerations.

Whilst the risk is huge I also see AI forcing us to be better, to create and manage data more effectively, to ensure our infrastructure is well architected and secure.

It is also critical to think ethically and responsibly around how we deploy AI in the right way. We all have seen recommendation engines in action with the likes of Amazon leading the way. A new focus on hyper personalisation means that companies can influence people based on the data they create, leveraging personal information to encouraging them to buy their products and services.

This creates a great deal of vulnerability …..almost like insider trading. This needs to be safeguarded against and we need to be cognizant of other criminal and ethical implications. Companies have a lot to do and they need to start now!

q As AI expands rapidly

can governments and regulators keep up?

I think they are certainly going to need help,

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particularly as there are very few experts and a lot of demand in this area. Governments and regulators will need to consult widely and engage with the tech giants, and industry leaders to help them understand and legislate accordingly.

We are already seeing governments create senior AI consultation roles to help design and write legislation.

Companies need to respond and create processes and governance to react to the market and the incredible pace of change. We need to have conversations around how we attract new talent into the sector to create not only the legislation but the ecosystem of experts to allow this industry to move fast but also move responsibly.

The legal profession is going to be transformed by this as smart contracts and e-discovery of documents are going to increasingly come into play. Ultimately bringing in controls with the right experts, employing the right people and seeking the right help, both from a legal and governance perspective is incredibly important.

q Has AI been overhyped or are we on the cusp of a technological revolution?

I think it's a possibility of both. Everybody wants to harness the benefits of AI and this has generated a huge amount of demand that, in itself, might almost be creating an overexpectation of what is

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possible to deliver within short timescales. That being said, in the next three to five years it is absolutely going to transform the world of work. I am in no doubt that a revolution is underway.

I’m dealing with a lot of clients who currently want AI but they do not know where to start. Companies don't often appreciate the amount of work that’s required to set up the infrastructure, to choose the right tools and to make good quality data flow to train a model or to leverage a chat GPT like interface.

Data is the new AI fuel and it needs to be managed, curated and crafted to ensure a trusted outcome.

What we are seeing now is that analytics and insights are gradually converging with infrastructure to support AI. There is obviously some hype and still a lot of work to do to make AI happen, however in three to five years, AI will be so embedded in our lives there will be no turning back. Will AI take your job?

Maybe not but someone who understand how to use AI just might!

q What industry or sector do you consider will benefit most from AI to create the greatest societal gains?

I think there's a huge opportunity in government.

If you think about how we interact with government and procure services, AI and generative AI

in particular, have the potential to produce much greater efficiencies and subsequently deliver improved services. How governments and local councils deliver services can be improved with intelligent AI powered applications. This can create an enhanced citizen experience and better social outcomes.

Health is another obvious beneficiary of AI in terms of automated diagnostics, better services, customer support and ensuring the patient journey and care pathways are fully optimised to deliver better healthcare and patient outcomes.

While government and health will clearly deliver significantly in terms of societal benefits, other areas such as ESG and sustainability will be impacted by AI. As data, machine learning, and AI continue to gain prominence, experts are raising concerns about the environmental costs of computation — primarily data and AI’s carbon footprint and greenhouse gas emissions. Cloud has a larger carbon footprint than the entire airline industry! I think the tech industry will have to move to green data centers faster and look at sustainable energy sources to power the AI revolution.

This move will eventually benefit us all and force an increased pace towards a greener future!

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Ruth McGuiness

The rise of data and AI at Kainos Ruth McGuiness, Head of Data and Artificial Intelligence at Kainos, explains how the sector has taken over the world and what should be considered when adopting AI in your business q In your opinion what has been the most impactful

developments in the Data & AI sector over the last 12 months?

Over the last 12 months, we've seen AI evolve from probably quite a niche, technical specialism into something much more significant in terms of societal and cultural impact, and this has transcended the public consciousness in a way few could have predicted. We’ve gone from being a niche team of specialists to being part of a much broader, global conversation around the application of technology, its potential societal impact, its ethical implications and whether we need to regulate it.

AI has completely transformed people's view on the future of work and everyone in every career is thinking, "How do I use artificial intelligence to work more efficiently and to get there quicker?"

q Kainos is scaling for growth. How much do you expect

this sector to grow and what impact will the investments in the advancement and scaling of Generative Artificial Intelligence (AI) have on the business?

Over the last number of years, there has been a massive undertaking within the company to scale AI skills across the entire organisation to ensure all our workforce is underpinned with a degree of that capability. We have had to think about how our software engineers use AI, how software testers test AI services and how service designers design a government service that's fundamentally underpinned by artificial intelligence.

The introduction of generative AI has been an accelerant and is going to be the real game changer in the industry, making AI accessible to more people than ever before. Some of those advancements in generative AI (such as GitHub Copilot) could

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be transformative to the software industry, automating elements of the software engineering process to free up engineers and allowing them to do more interesting and challenging work. For Kainos, the latest £10m investment in generative AI is off the back of 10 years of investment, and the next iteration for us is how we leverage technology to work smarter and to work differently.

q Kainos is also increasing investment into the funding of academic research institutions such as the AI Research Centre (AIRC) at Ulster University. How important is it to retain and develop relationships between Kainos and Universities in Northern Ireland?

A big focus of the investment in AIRC with Ulster University is around furthering our understanding of how to implement artificial intelligence responsibly, and further research centres will be established throughout this calendar year.

I recently spoke at the Northern Ireland Investment Summit alongside Máire O'Neill, who heads up ECIT and Queen's University's cybersecurity unit, and we recognised that what actually makes Northern Ireland unique is the incredible bond between industry and academic research. If we are going to solve big societal problems and solve the problems our industries face, I don’t think we can solve those problems alone. We absolutely need the support to leverage the brilliant minds within our academic institutions.

The relationships we have with our universities are also really important to help shape the future skills that we need for the entire technology industry in Northern Ireland.

q What is Kainos' approach to

ethical and responsible AI?

Kainos has been growing its data ethics capability for several years, and being a leading partner for AI services to UK Government comes with great

responsibility. We must build services that have a positive impact on the citizens that use them; ensuring we use emerging technology in a responsible and ethical way.

For every project we undertake, we follow a data ethics framework to check each key stage of the project – making sure the use case is responsible and free from potential ethical concerns.

This includes potential biases that can come into the process for an existing use case or if it is repurposed for some other reason in the future, we can mitigate potential concerns.

Kainos also has regular engagement with industry partners like Responsible AI UK, Microsoft and AWS on leading approaches to ethical AI. Making sure that we're constantly bringing that into how we work and how we deliver for our customers to ensure we are building technology for a fairer and more responsible world.

q As one of the only people in the UK and Ireland to join and Microsoft's global partner Advisory Council for data, can you tell us what this involves?

The council meet twice a year in Microsoft’s Redmond headquarters in the US, providing Kainos with a very privileged position to get the latest view of the AI product roadmap and take part in discussions around future functionality and features. It's an advanced introduction to what's coming to the market, not just for Microsoft UK, but Microsoft globally – which is really exciting to be part of (particularly when you consider their position at the forefront of generative AI alongside open AI globally).

This also provides Kainos with the opportunity to give feedback in terms of how we feel about these features and what we think the impact will be, while at the same time preparing our teams internally to respond to the technology once it's made available for us.

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q Looking ahead, what will be the key drivers for growth in AI?

There are obvious considerations around responsibility, and global governments are moving fast to regulate AI. As a result, AI is becoming not just a technology discipline, but an industry in itself - so we will see growth in areas of AI regulation and legal services. Deploying artificial intelligence in a responsible and ethical way to avoid harm and bias is going to be an industry in its own right so obviously, there's going to be huge growth in that space.

We will see growth in the adoption of tools like ChatGPT and CoPilots, and AI productivity tools that are readily available off the shelf and don't require investment. I see a fundamental shift in skills; not just technology skills, but all skills as all industries will be impacted in every way.

There's a global arms race between Microsoft, Amazon, Meta and Google around advancing the capabilities of these technologies - and that's creating a bit of a monopoly. I think you'll see a shift from organisations building their own AI technology to the adoption of these kinds of global hyper scaler tools.

q As the business grows and your teams expand, what skills will you seek to attract to your practice?

12 months ago, I would have said a background in statistics, mathematics and computer science (or a wellrounded technical background at least). But going forward, as AI becomes more of a moral and ethical discussion, we will require more diverse skills. Not just diversity of who you are - but also in how you think.

Be that from a philosophy or arts background, we are looking to reskill those individuals to be a technical and ethical hybrid. Ultimately, we are looking for people with a passion for artificial intelligence and a passion for solving big global problems.

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Russell Sloan

Welcoming Kainos’ new CEO Russell Sloan will take over from Brendan Mooney, CEO of 22 years, with the pair working together to prepare for the transition. We sat down with Russell to find out more about his journey here and his future at the company q As CEO and successor to Brendan Mooney, did you

ever envisage you’d be in this position when you first joined the business as a graduate software engineer 24 years ago?

I joined Kainos as a fresh-faced graduate straight out of Queen's University and my priority was getting a job in Belfast without really thinking too far ahead. While completing my Masters in Electrical and Electronic Engineering, I became more exposed to the elements of management and I gradually evolved away from a purely technical route, progressing into leading and managing teams.

The accelerator for my career journey came at the end of 2012 when I was asked to look after our fledgling Digital Services business unit. I started leading a team of 35 people and by the summer of 2023, I had around 1,600 people delivering complex digital transformation projects across UK

government, healthcare and commercial sectors.

Did I ever expect to be CEO? I guess in the early days, the answer would have been no. People can dream of those things, but back then I didn't really think much about it.

We had a four-year transition plan that started back in 2019; established when a small group of Kainos’ most senior figures attended a two-week course at Stanford University. After that, I started attending our Board meetings and became more involved in investor relations with Brendan. Slowly, I was starting to get exposed to more and more aspects of the role.

It's been a really structured and well-thought-out transition plan, but I don't know if it ever prepares you for that moment when the phone rings to say: "It's time!”

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q The word ‘Kainos’ is derived from the Greek word for new or fresh.

Given the business was established over 35 years ago, how does Kainos remain new and fresh in today’s market?

Looking back to the late 80’s and 90’s, Kainos developed and delivered largescale software engineering projects such as the London Underground ticketing system and a point-of-sale application for Marks and Spencer.

From 2010, we started to focus more on digital transformation and ever since we’ve been reinventing the possible through digital innovation. In terms of staying fresh, we invest in learning to ensure we remain at the forefront of innovation – whether that’s using AI and deep learning, experimenting with augmented and virtual reality, or adopting intelligent automation. We also take on a lot of graduates each year, introducing new thinking into the organisation.

q Recognised as NI’s most successful software company, Kainos has experienced explosive growth in revenue and headcount over the last decade. What do you envisage are the greatest challenges and opportunities for the company over the next 10 years?

In the short to medium term, I think a lot of organisations are still looking at how working patterns are changing.

We’re seeing a dynamic shift in occupancy rates across our offices so we are making sure our spaces are collaborative, accessible and inclusive.

We have already updated our Belfast, Birmingham and Indianapolis offices with this in mind with Toronto and Gdansk due to follow later in the autumn!

As we head into the future, generative AI is going to impact all roles. So, there's a challenge to adopt this technology quickly; taking on some of the new work practices as well as the opportunities that will manifest as the technology develops.

Another area of immediate focus is green software engineering. We have committed to being carbon net zero by 2025 and we’re well on track to achieving this goal. We've also made a Green Software Commitment to our customers and the environment; meaning from now on, everything we design and work on will use green software practices. Implementing carbon-aware software services is a crucial step to reducing environmental impact as well as meeting climate and sustainability goals.

q We all heard about ‘The Great Resignation’, meanwhile Kainos maintained a well above average industry staff retention rate – what is it that makes people want to stay and build their careers?

I might be slightly biased due to the fact I’ve been in Kainos 24 years - and it’s the only job I’ve had since leaving university! But I’m sure most of my colleagues would agree with me when I say it’s all about the people. We have some amazingly talented people in the business, and a special culture of going the extra mile to support each other and our customers.

When you get challenging work and the opportunity to work alongside really great people, there is a natural tendency to be engaged in what you do and, ultimately, deliver some great, cutting-edge outcomes. The work here is enjoyable and challenging – and it will push you to be your very best.

q With 34% of women employed

in the business against an industry average of just 20%, how important is diversity and inclusion to Kainos and its success?

Gender diversity is an easy one to measure and it's great to see we're making progress in this space – but we have more progress ahead of us as we commit to enhancing female representation across Kainos. We also have different employee groups around ethnicity, LGBTQ+, neurodiversity and

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disability. These groups are consulted on key strategic decisions, providing unique viewpoints which help shape Kainos now and in the future. One thing that is difficult to measure is diversity of thought. For me, this is one of the most important things within a business.

Encouraging those different ideas is the key to success – particularly as we think about some of the challenges we face around AI, ethics in AI and the impact on our solutions. Different backgrounds provide different angles and insights to deliver better outcomes, for our people and our customers.

q Generative AI has dominated the headlines over the last 12 months.

Are we truly on the cusp of a new technological revolution and what could some of the more positive outcomes for society look like?

As far back as 2015/2016, we started looking at how AI might impact us as a research topic. We now have a dedicated team of 200 people in our Data and AI practice who are already delivering real value for our customers by incorporating AI as part of the solution.

Generative AI will allow space for additional thinking time and will absolutely change the way that people work. It has the potential to remove a lot of the more mundane tasks, allowing people to focus on more interesting things that can add value for themselves and for customers.

Thinking about AI more broadly, one simple and real example I would give you involves some of the work we do with the National Crime Agency, specifically around child sexual abuse referrals. It’s a startling fact that currently over half a million people in the UK are deemed a threat to children.

Using AI, we've managed to reduce their referral time from 45 minutes down to two minutes when a child has been potentially detected at risk. So yes, overall, I think AI will be somewhat revolutionary and will have numerous positive impacts on society.

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With the continued growth in big data opportunities, organisations that strategically invest in and optimise their IT and network infrastructure will be the ones primed to harness the transformative potential. Here, we speak with three experts from eir evo on how organisations grappling with massive data volumes can ensure effective data storage, accessibility, scalability and security

Jim Montgomery, Digital Transformation Business Development Lead

q With the growing emphasis on real-time data analytics in big data, are there any data networking best practices or technologies that should be prioritised?

The potential value of big data is immense but it does depend on being able to analyse and derive insight from it in real-time. The network is the foundation for delivering the required performance and there are four critical components to this: latency, bandwidth, redundancy and monitoring.

Defining ICT infrastructure for big data success

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Low latency across the network is paramount to faster transaction times, improved application performance and freeing up processing resources.

When dealing with real-time data, a high latency or delays could mean the difference between success and failure.

In terms of bandwidth, speeds of 100G and up to 400G are commonly deployed within and between data centres and technologies such as MPLS, DWDM and Point to Point Fibre provide the required high bandwidth wide-area-network connectivity.

Building network redundancy into every layer of the design means that, even in the event of failure, data can keep flowing and when one device fails for instance, another can automatically take over. Lastly, employing monitoring tools allows for quick issue identification and network automation allows the network to adapt to congestion, delays and failures dynamically reducing the time to resolution.

q Data security is a significant concern. Could you highlight specific networking technologies and protocols that are essential for securing data in transit?

To enhance data security in transit, organisations must ensure three fundamentals are adequately incorporated into the network. Firstly, end-to-end encryption of the data by implementing protocols like IPsec and SSL/TLS. Secondly, using firewalls and intrusion detection/prevention systems (IDS/IPS) to monitor and filter network traffic. Thirdly, ensuring strict access controls to protect sensitive information in transit.

In big data environments, these security fundamentals are integrated by implementing them at various levels of the data pipeline. For example, encryption may be applied to data at rest and in transit between Hadoop clusters using SSL/TLS. Firewalls and IDS/IPS systems are set up to

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monitor traffic between data nodes and external sources. Access controls are applied not only to data storage but also to data processing frameworks.

Failures in implementing these can result in data breaches, compliance issues, and reputational damage so a comprehensive and well-managed security strategy is essential for organisations dealing with big data.

transformation and loading processes.

q Data integration is a key challenge in big data projects.

Can you share insights on how data network design can facilitate data movement between diverse sources?

A well-structured network infrastructure facilitates data integration by efficiently and reliably connecting data sources, often between geographically dispersed data sources, for seamless data transfer. It is characterised by high bandwidth, low latency and critical security measures like encryption. However, a wellstructured data network is also built with inherent scalability to adapt to growing data volumes and additional data sources without degrading performance.

To facilitate data movement between diverse sources, properly configured data routers and switches enable intelligent data routing based on predefined rules. This allows organisations to direct data to the appropriate processing or storage systems for integration, enhancing efficiency and reducing the risk of data loss or duplication. With QoS mechanisms, organisations can prioritise data packets based on their importance and the criticality of the data integration task, meaning those with high priority receive the necessary network resources for optimal performance.

All of these are fundamental characteristics for building robust data pipelines, that will allow for the automation of data ingestion,

John Doyle, Director of Managed Services and Cloud

q Can you explain how public and

private cloud services complement each other within an organisation's IT infrastructure strategy and how they can be optimised in big data initiatives?

The choice between on-premises, public cloud, or hybrid deployment for big data solutions depends on several factors. On-premises offers full control, data sovereignty and predictable costs but limited scalability and high initial outlay for hardware, software, and infrastructure setup.

On the other hand, public cloud offers scalability, cost efficiency and the availability of managed services and is suitable for variable workloads and for organisations looking to offload infrastructure management.

A hybrid approach is ideal for achieving the balance between on-premises control and cloud scalability. Hybrid solutions are beneficial when dealing with legacy systems, sensitive data, or specific compliance requirements and provide for additional redundancy and critical data backup. Ultimately, the best choice often involves a careful evaluation of your organisation's specific needs, budget constraints, and long-term IT and big data strategy.

q Data backup and disaster recovery are paramount for business continuity. What best practices should organisations with diverse data environments consider when leveraging cloud services in big data scenarios?

Organisations can establish reliable and secure backup and disaster recovery strategies, either within a public cloud or by incorporating private cloud options such as eir evo’s Digital Planet for added redundancy and control.

These strategies should incorporate documented policies around backup frequency and retention, aligning with compliance requirements; automated backups to ensure consistency and reduce human error; regular IT staff training on back-up procedures; and data redundancy facilitated by the cloud provider's replication features, including across regions.

Remember backing up within a cloud to a different region within the same cloud is a good option but it carries some risk as the data is sitting within the same cloud. There are options on private cloud or alternate hybrid cloud backups that give an extra layer of resiliency.

When it comes to costs, you can optimise these by choosing suitable storage tiers and efficient data transfer methods and by periodically reviewing and removing unnecessary backups.

q How can organisations monitor

performance and ensure optimal resource allocation and scalability for their data processing needs in the cloud?

Monitoring with alerts on resource usage anomalies can help identify areas where resources are over-provisioned.

Implementation of resource tagging allows organisations to track costs by department or project and educating teams can help with efficient resource usage.

Automation can be utilised to scale resources up or down based on demand, keeping costs low by ensuring

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resources are active only when needed.

To further save costs, consider spot instances (cloud) or preemptible VMs for non-critical workloads - such as testing, rapid batch processes, and fault tolerant systems - and using optimised storage tiers (Cool, Archive) and serverless options.

To help organisations confidently manage their budgets, we offer expert guidance on cost-effective licensing strategies, including considerations for volume purchasing, optimising software bundles and potential savings during license migration to the cloud.

However, while cost optimisation is essential, we prioritise maintaining high performance standards to ensure clients get the most value from their cloud investments.

get started more efficiently but scale to the capacity needed in a secure and governed manner. Leaving you with a modern footprint for data, managed by Azure - allowing your teams to focus on productivity, and leveraging the power of a modern data estate.

q Scalability is crucial in the

context of growing data volumes.

Can you explain how Azure's auto-scaling capabilities can be integrated into an organisation's IT infrastructure strategy to efficiently handle increasing demands for big data processing?

Joe Carlyle, Microsoft Practice Director

q As Microsoft Ireland Azure Infrastructure Partner of the Year, can you tell us how organisations can leverage Azure's cloudnative services to enhance their IT infrastructure for big data initiatives, and what are the key advantages of doing so?

Adoption of Azure brings with it two key benefits – scale and security.

Leveraging cloud native solutions, like Azure Synapse, allow you to not only

A move to cloud, more specifically Azure, brings with it a shift in thinking.

Gone are the concerns around your fixed capacity SAN, or performance limitations of your hardware from a few years ago. The focus now shifts to requirements versus cost. Azure has near-infinite capability to offer the elite performance and storage that you may need, and this is often enticing for developers, data engineers etc.

However, just because it can now complete an action in 10 seconds, rather than 120, doesn’t mean the business needs that. And often more importantly, can the business afford it? Integrating this shift in thinking, and frontloading all design and planning efforts ensures this will not become an issue, simply part of the process.

q Data governance and compliance

are vital. How can Azure's compliance and security features be effectively incorporated into the IT infrastructure to ensure data governance, protection, and regulatory compliance throughout the big data analytics lifecycle?

Adoption of Azure not only brings with it cloud-native data solutions, it also brings native integration to massively scaled security solutions such as Microsoft Defender for Cloud, and core governance services such as Azure Policy. Leveraging the core controls of Azure, which includes both of these services, via a correctly planned and designed Azure Landing Zone is vital to ensure successful security and governance. Combining this all together with Azure Monitor allows you to report on your compliance in real-time, and remediate gaps with minimal effort if they appear, thereby ensuring your required standards are reported on and adhered to.

eir evo designs, delivers and manages end-to-end digital infrastructure from edge to cloud for businesses of all sizes and as tier-1 partner with many leading technology brands including Microsoft, HPE, Cisco and Fortinet, is committed to helping organisations across Ireland, North and South, to get the most of their technology investments.

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Ger Connery

Don’t overlook the data behind comms Ger Connery, CEO at Sentel, expands on how essential data-driven decision-making is when communicating in your business

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mall business owners in the UK are being urged to develop their employee engagement strategies after a report found that 9 out of 10 UK workers are disengaged with work (Young, 2023). We asked communication professionals for their thoughts on how organisations can use communication data to drive better performance and increase employee satisfaction.

It’s time to assess your communication channels strategy and tailor your approach. New year means new challenges.

Strategizing for 2024 will be particularly important given that 76% of UK respondents to Gallups’ engagement survey described themselves as being not engaged. (Gallup, n.d.).

Gallup estimates that low engagement is costing $8.8 trillion globally! Anna Sawyer, principal partner at Gallup, encourages that there's a huge opportunity for organisations to unleash

their potential, so what can the data tell us?

Communication analytics can provide a wealth of information that will help organisations derive insights and improve their performance. By utilizing the data behind fixed line, mobile, video, email and chat comms, organisations can get real information that will help drive their comms strategy whether internally to create efficiencies and positivity or externally to improve customer experience.

Take call handling on fixed line for one. Ask the business, do we know how many calls we are handling? Do we know how many calls are being missed on fixed line and MS Teams?

Are these calls being returned? Are staff too busy on internal MS Teams calls that they are missing important customer calls and does this lead to employee dissatisfaction? Are we measuring call traffic against key metrics on response times

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and duration? All this data helps identify trends and the ability to put measures in place and make datadriven decisions to optimise performance and outcomes.

This type of data will give the evidence and insights to address any communication weaknesses.

right results? Teams chat might get a quicker decision for example, or long chains could move to a channel chat perhaps instead of email for quick decision making. Continuous data will allow the business to meet evolving comms needs and stay aligned with goals.

Collaboration tools like Microsoft Teams have skyrocketed, especially as remote work and hybrid work environments have become more prevalent. With more than 270 million users, MS Teams is the most popular business communication platform in the world (Digitalwell, n.d.). While these tools are incredibly useful for team collaboration and communication, employers may wonder how employees are using MST’s, activity, and productivity wise, internal and client side. Workplace analytics!

The extent of tracking depends on the organisation’s policies and privacy regulations. It would be important to maintain a balance between monitoring and privacy for most. It could be a problem with certain organisations regarding privacy and excessive monitoring. It’s up to each organisation to establish, communicate and respect their own company privacy rules. If a user utilises private or public chats how are these handled?

Therefore, a baseline approach to reporting initially is required so as not to exclude those organisations wanting to avoid intense employee scrutinizing.

How popular is MS Teams and Zoom in your organisation post-pandemic?

We need to gather and analyse the data across all the channels including email, chats and calls in a coordinated approach so that we can identify patterns, trends and ultimately areas for improvement across the business. Analysing behavioural insights like comms patterns and how individuals and teams communicate can help create strategies that optimise for maximum effectiveness, reduce bottlenecks and improve workflow efficiency.

Collaboration results and patterns - are employees using the right tools for the

Employers should communicate clearly with employees about the extent of monitoring and tracking in MS Teams, including any third-party tools that may be used. Ideally, employees should give informed consent to any monitoring or tracking that takes place.

Employers should make it known to the employees that the use the data collected from Microsoft Teams and other channels is to improve overall team productivity and collaboration, rather than focusing on individual

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employee performance or using it to micromanage.

efficient way of working?

It’s so important that organisations understand how different communication channels, messages and interactions impact the business goals, enabling refinements for better efficiencies and external customer engagement. Soon, AI and machine learning will automate routine tasks and analyse these vast amounts of data to provide predictive insights for more informed decision-making.

By looking at meeting hours data by number of attendees by duration, Managers can help teams build better ways of collaborating and better habits to contribute to a better working life. Do Managers attend meetings with employees for coaching and mentoring?

It’s important to understand that focus time data. Are employees moving away from screen time for wellbeing focus? Are team leaders actively encouraging breaks?

HR strategy

Data provides powerful insights for data-driven decisions for HR and strategy. Users will have a powerful tool to address challenges in HR, employee engagement, protecting work-life balance, employee efficiency, general performance efficiencies - operation time spent etc. Employers can protect work-life boundaries through reporting on employee numbers that are collaborating outside normal working hours and patterns and trends of employee engagement. Does the organisation need to change strategy, for example offering flexible working hours as comms data patterns show most work employees interact between hours of 10am and 7pm?

Taking it a step further, we can look to analyse how employees are working, remotely and hybrid. Does this change over time? Do we need to change strategy to suit? What would be a more

Make meetings effective

Utilise the data to make meetings effective and drive positive changes. We can see that you are working beyond core hours 59% this month therefore….

Cancel or shorten meetings on review. Analytics can provide some surprising results here, you may find employees are engaged for a longer portion of their week than expected in certain meetings. Results of changes can be measured over time. Are efficiencies improving? What were the benefits of that change we made by reducing daily meetings to 3 a week instead of 5?

A mixed approach to access employee engagement, customer experience and internal comms is best.

It’s vital to use the data alongside qualitative methods to get that deeper insight into your customer and employee behaviours.

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Danske Bank: Data-enabled digital transformation Lyndsay Shields, Head of Data and Analytics at Danske Bank in Belfast, explains the role of new tech and data in banking

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hange is apparent everywhere, but one of the sectors where digitisation is most obvious is banking and financial services. As banks digitise and transform customer journeys and customers interact more and more with digital channels, making sense of those interactions is increasingly important.

The team’s mission is to make banking easier, leverage data and drive more value from it to improve products, services and experiences for customers and colleagues.

“The pace of change in financial services is rapid and we need to be agile when it comes to the skill sets required to keep up with those changes,” says Lyndsay Shields, Head of Data and Analytics at Danske Bank in Belfast.

“The aim is pretty simple – to know our customers through data and make that knowledge available to colleagues in the organisation who can use it effectively to support customers or improve the business,” says Lyndsay.

Lyndsay heads up a team of 25 working across data management, data architecture, business intelligence and analytics, and business analysis.

“But the actual delivery of that objective is less simple. It involves focus right across the data value chain and everything from engineering and architecture development, knowing how information flows through systems and applications right through to equipping colleagues with the skills to analyse and interpret dashboards.”

“There are roles today in the bank that didn’t exist two years ago. In data, we have evolved from having analysts and developers to now having engineers, data scientists and data architects. The team sits alongside API developers, coders, business analysts and other roles you might not traditionally expect in a bank- and it is evolving all the time.”

Having analytics at their fingertips helps the bank understand and predict what customers need, helping its people to make faster decisions.

Unlocking the value of data

Danske’s Data & Analytics team has grown in size and capability since the Technology & Digital Development

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department was set up two years ago, headed up by Chief Information Officer Liam Curran.

Lyndsay, who has had a long career in Danske Bank and has held strategic roles in business transformation, change management and customer experience, says the team has a blend of different skills and experience.

“Whilst there is obviously the very technical side to working with data, it is actually a business topic. It is about how we use data to improve our products, and processes to make things better for customers,” she explains.

“We have been very deliberate in putting the team together. As we are on a transformation journey, we need really skilled technical people with external experience but we’re a data team embedded in a bank, so we also really need to know the organisation we’re working in. So, we also have people who have worked in customer-facing roles and can navigate our processes and systems easily, who have reskilled to become developers and engineers”, says Lyndsay.

Artificial Intelligence

It is impossible to talk about data transformation without bringing AI into the conversation, such has been the hype about generative AI. Danske is investing in a number of use cases, while also being mindful of the ethical considerations of AI and its limitations.

“AI has actually been around in the bank for years. We use AI in lots of our processes, like transaction monitoring and fraud detection.

Generative AI is the new kid on the block and we are seeing huge potential to use it to improve customer and colleague experience,” explains Lyndsay.

“We’re looking at AI as another tool in our toolbox to enhance customer experience and act as a copilot for colleagues. We’re starting with “human in the loop” use cases so we’re not releasing the AI completely to the customer where there is any complexity involved in the process, but for low-risk engagement tasks or where there’s a human safety net.”

The team is also working with analytics counterparts in Danske Bank Group who are developing large language models and is working on its own version of Chat GPT. “That’s very exciting. It will be used for back and forward conversation style processes to free up adviser time,” says Lyndsay.

While Danske Bank wants to use data to help replicate human interactions, it is conscious of its responsibilities and takes a “data for good” approach.

“When a customer shares their data with us, that is done with trust. We don’t share that data, we don’t sell it. We treat it very carefully.

When we talk about value from data we mean

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customer value, operational value for colleagues and using it to improve products, services and bank performance,” explains Lyndsay.

process to how we set the criteria, to the interview panels, that it is as genderless and accessible as possible. That encourages a balance of applicants.”

“For example, we’re in a cost-of-living crisis and one of the projects we delivered recently was looking at customers’ financial wellbeing to predict where they might be heading into difficulty early on before they know it themselves, through early behavioural triggers.

That information is passed to skilled advisers who can reach out proactively and help them.”

The focus on diversity is one of several reasons Danske has topped the prestigious Best Place to Work list in Northern Ireland and was recently awarded the Business in the Community NI Responsible Business Award for Diversity & Inclusion. The Bank continually invites feedback from employees in order to keep improving.

Diversity

In addition to bringing in team members from diverse backgrounds, Lyndsay is passionate about getting more women into technology roles and is a co-chair of Danske’s Gender Diversity Network.

It’s an industry challenge, and while Danske’s technology team is ahead of the industry average in terms of its female-to-male split, Lyndsay says it’s about more than numbers.

“We see opportunities for more women in senior roles, driving representation at the more senior grades and in external technology and data recruitment where it is still more heavily weighted to male applicants,” she says.

“Talent will get the role.

What we ensure is that the end-to-end process – from how the job advert is written, to the recruitment

The bank’s approach to skills development and career support is also innovative, with mentoring and development days offered alongside more structured training programmes, such as apprenticeship programmes where colleagues can learn on the job while studying for a third-level qualification, or its Digital Academy, which enables colleagues with an interest in data and technology to be seconded for 6-9 months to get experience they can take back to their teams or use to apply for new roles.

Lyndsay adds: “There are endless opportunities within Danske and a number of different learning and growth pathways. Colleagues can progress their data career, for example, from entrylevel to senior technical roles or leadership. As an organisation, we are well placed to stay agile and keep moving with the industry.”

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Data literacy: Why it matters for your business Sync NI sat down with Liberty IT’s Steven O’Kennedy, Director of Architecture Data and Cormac Bradley, Senior Data Solutions Architect to find out about the importance of data literacy and the impact it can have on businesses

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ogether, Steven and Cormac have over 40 years’ of experience in the tech industry. They will be taking to the stage at the Big Data Belfast Conference to discuss the impact and importance of data literacy for the modern enterprise.

Steven is part of Liberty IT’s architecture group, working primarily in the big data space for the industry leader in digital innovation’s parent company, Liberty Mutual’s, commercial insurance business. He helps to create an efficient set of data capabilities that allow the business to make decisions quickly.

Over the last decade, Cormac’s primary focus area has been across the data space. He currently supports a number of teams working on Liberty Mutual’s Data Science Platform.

These teams are focussed on delivering key data science capabilities empowering consistent adoption of MLOps across a diverse range of domains in a secure manner.

Sync NI sat down with Steven and Cormac to find more about

the importance of data literacy and the impact it can have for businesses.

q Is there evidence to suggest organisations have a

problem to data literacy?

A number of industry surveys conducted over the last five years have consistently shown both the existence and persistence of a Data Literacy skills gap.

There has been a sustained consensus among C-suite level respondents on the importance of data literacy for business, 89% of whom expect team members to act based on data informed decisions. There is, conversely, a lack of confidence across all workers in their fundamental data skills - only 11% of staff have confidence in their ability to work with data hence the Data Literacy skills gap.

It is also worth noting that this gap even exists among decision makers - junior managers and above - only 24% of this cohort have confidence in their ability to read and

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understand data.

Current data training tends to be focussed on tools and largely targets data specific roles - data scientists, data analysts and directors etc. This results in a skills and enablement disparity which can give rise to bottlenecks in decision making or pursuit of instinctive decisions.

q What impact can data literacy have on a business and its employees?

A Gartner report has predicted that only one-third of companies will have achieved data literacy among their employees by 2023, resulting in a competitive disadvantage for companies lacking these skills.

This competitive disadvantage manifests across revenue, profit, customer satisfaction and loyalty and employee productivity.

Companies with a thriving data culture and data literacy programme all improved by between 17% - 20% across each of these areas. Staff retention has also improved for businesses where data literacy skills have been rolled out.

Data literacy has a tangible, realisable impact on a business.

Moreover, the benefits of Data Literacy extend beyond the business to all employees as well - it is estimated that staff members with proven data literacy skills can command a salary increase of up to 20%.

q What are the key barriers to improving data literacy?

There are a number of socio-technical barriers impeding data literacy improvements.

Data literacy is an enabling step towards organisational cultural change - shifting a business from traditional means of working towards being a data informed and driven business. Cultural change is hard, taking both time and

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focussed programmes to overcome innate organisational resistance to change.

Executive sponsorship of a programme is key with regards to driving data literacy initiatives, ideally these would be a key pillar within the data strategy.

Other challenges include awareness and understanding of what data literacy is.

For example, it isn’t simply working with data, numbers and statistics - it spans a broad set of soft and technical skills.

Moreover, these skills are role and level specific - there is no one size fits all.

Clearly articulating the breadth, depth and variety of skills encompassed by data literacy, the range of learning pathways - and the purpose and value of these learning journeys - is another critical facet in removing barriers.

Lastly, truly empowering teams and employees to embrace data literacy requires supporting technical capabilities to be in place e.g. tooling enabling easy access to data, while ensuring regulatory compliance, is critical, as is tooling supporting working with data - from analysis through to visualisations and reports.

q How can organisations best bridge the data literacy deficit and instil a data culture?

Highlight the value of data - and the role played by data literacy in unlocking this value, for all teams - is a critical step. As per above, this can start with a clear articulation of Data Literacy and how it relates to specific roles and level within an organisation - this helps highlight the relevance of Data Literacy for all.

Education, training and support are the key building blocks of a data culture based on data literacy. Education and training should be viewed and enabled as perpetual learning - with appropriate learning paths and feedback supporting this by mapping out routes forward for employees. Variety in education

Liberty IT's Steven O’Kennedy and Cormac Bradley

and training materials is important self-serve learning materials should be supplemented by workshops and presentations.

Many organisations have found using “champions”, data literate experts, is a successful means of promoting Data Literacy.

Lastly, provision of tooling to make data access and working with data is a central underpinning for a successful data literacy programme.

q What methodologies and tools should data scientists embrace in the age of AI?

It’s an unfortunate cliche, but as often, it depends! This is often going to be very specific to both a data scientists workplace and also their particular domino or expertise.

The boring answers still hold true here - as much as possible sticking to tried and trusted tools will mean a broader breadth of community knowledge and support can be drawn upon. A clear grounding in the fundamental methodologies of data science and machine learning continue to form the foundations of successful data science in the age of AI.

q What role do cloud technologies have in realising greater value from ‘Big Data’?

The key capabilities of cloud technologies, when used appropriately, continue to play a key enabling role in realising great value for Big Data.

These capabilities include scalability, cost-effectiveness, agility, security and integration.

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Pete Wilson

“Shaping” the 4th Industrial Revolution with CGI We spoke to Pete Wilson, Programme & Delivery Director at CGI here in Northern Ireland, who has over 30 years of tech delivery experience

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ete’s focus is on bringing the latest advanced technologies to bear such that CGI’s clients can remain both relevant and competitive. As a former WEF 4th Industrial Revolution ‘Shaper’, he is particularly enthusiastic about how AI and automation can deliver benefits to business and society at large.

revolution, and the recent public emergence of Generative AI technologies like ChatGPT has notably captured the public's attention, prompting a keen awareness and interest. The huge advances that we’ve made in the fields of Big Data, AI & Automation, and the commercialisation of these advances are really starting to gain traction and will undoubtably impact on the world of work in the coming decades.

Founded nearly 50 years ago, CGI is as one of the world's independent largest IT and business consulting firms. The firm has been busy expanding its growing UK business into Northern Ireland by extending its Digital Services Delivery Centre into Belfast, adding to its existing workforce of over 6,000 people throughout the UK. Through this new Belfast centre, CGI is expanding its client base in both the public and private sector across Northern Ireland, adding to a portfolio of clients throughout the UK and Ireland.

Here in Northern Ireland, we are very proud of the availability of a highly skilled and educated workforce. We know that many professionals have received world-class training and education which makes them well-suited for AI and automation-related roles, both in terms of working with, and delivering, AI related solutions. CGI’s decision to build out its growing Digital Services Delivery Centre is also based on Northern Ireland’s geographic location with strong connectivity to both the UK and the Republic of Ireland, great R&D opportunities, and its proximity to its key markets.

q Why has CGI come to NI?

Northern Ireland is strategically well positioned to engage in the transformative shifts occurring in both the business and societal landscapes, primarily driven by the Fourth Industrial Revolution (4IR). We are currently in the initial stages of this

q What is CGI’s perspective on the deployment of AI & Automation technologies?

The world of work is on the brink of major transformations thanks to the advent of process automation powered by

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machine learning and predictive analytics. As a comprehensive technology and consulting company, we are actively collaborating with our clients and partners to not only implement these technologies effectively but also to ensure that their advantages resonate with both our clients' customers and their workforce.

One of our key focuses is on ensuring that we work alongside our client’s domain experts in capturing not only the routine processes that can be automated, but also the ‘edge cases’ that call on staff intuition, gained over many years. We are very aware that there are limits to what can be automated in organisations, and our approach is to explore those limits along with our clients.

q Why is it important to adopt AI and Automation? Is it feasible to disregard these technologies and stick with what we know?

Neglecting AI and automation in the workplace raises several moral and ethical concerns. It can be viewed as discriminatory or exclusionary, as these technologies enhance workplace accessibility and inclusivity for individuals with disabilities. While automation may replace certain jobs, it also enhances the quality and safety of work, making the avoidance of it an ethical concern, potentially exposing workers to dangerous tasks.

Furthermore, failing to embrace automation results in costly inefficiencies and resource wastage.

In a world with finite resources, choosing not to optimize processes and reduce waste may be considered morally irresponsible. There are other ethical considerations, including stifled innovation, missed opportunities for reduced energy consumption, and decreased global competitiveness.

Perhaps most importantly, we must consider the impact on employee wellbeing. Automation alleviates workloads

and reduces stress for employees.

Neglecting its implementation can have adverse effects on employee mental health.

q What are the key challenges that

you face in terms of driving progress via automation?

Automating business processes in the workplace offers numerous benefits, but it also presents several challenges. Firstly, there's the initial cost and time investment required for selecting, implementing, and integrating automation tools.

In addition, resistance to change among employees is a common hurdle.

Employees may fear job displacement or may struggle to adapt to new technologies. I often hear that certain processes and function requires “human intuition, built up over many years of experience and it can that can’t be automated”. Not all business processes are easily automatable. Processes that involve complex decision-making, creativity, or human interaction can be challenging to replicate with automation. Striking the right balance between human and automated tasks is a constant challenge.

While automation offers significant advantages, addressing the challenges of cost, employee resistance, data security, integration, process suitability, and ongoing maintenance is essential for successful implementation in the workplace.

q Can you give us some examples

of what CGI is doing in the Digital Transformation space?

Absolutely. We worked with HMCTS to launch a new digital service to improve the juror summoning process in England and Wales. It has transformed the way citizens respond to their summons for jury service.

The jury summoning process was very paper intensive. Summons letters were sent to all potential jurors and

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follow up communications were made by telephone, email, and post. User research found that many citizens would prefer the option to reply to their Jury Summons online, in line with their expectations of a modern public service.

So a new service was designed in line with the government service standard.

This directly supported the HMCTS transformation programme for the courts service across England and Wales - to modernise and simplify the justice experience for citizens and staff.

The service has been deployed to all courts in England and Wales and now enables citizens (including appointed helpers) to reply to their Jury Summons online through a web application hosted on gov.uk on their own phone, tablet, or computer.

Benefits include citizens making fewer errors when replying using the digital service, lower printing and postage costs, increased used of the available online materials to help prepare for jury service, and HMCTS Juror officers completing their work faster and spending less time correcting errors on summons replies.

In a further example of a groundbreaking use of AI and analytics, we are working with Ordnance Survey in Combe Martin, Devon with the aim of improving beach water quality, previously rated as "poor" due to sewage and fertilizer contamination. CGI is using AI and sensors along waterways to detect and prevent pollution. The AI model combines sensor data and satellite imagery, achieving a 91.5% accuracy in predicting pollution, promising cleaner water for locals and tourists.

Such examples are proof of how AI and automation can benefit business, government, and citizens. At CGI, we continue to invest in these technologies through our Emerging Technologies Practice and we look forward to bringing this expertise to the citizens of Northern Ireland.

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US-based company ESO opened its engineering hub in Belfast in 2019, with the 116-strong team responsible for developing software that supports emergency services across North America

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SO harnesses the power of data to identify trends and insights that support fire services, paramedics, and hospital emergency departments to become more efficient, ultimately improving the health of the communities they operate in.

Digital data is an increasingly powerful tool for the healthcare industry, connecting providers like ESO to large hospital networks and other healthcare facilities to support the development of new services and the optimisation of processes, along with enhancing medical research and early detection for improved patient outcomes.

ESO Belfast’s expertise has played a pivotal role in driving the company’s success over the past three years.

Now boasting a global customer base, numbering in the thousands, ESO stands as the industry's largest software company in the healthcare data space.

By analysing data trends across various Emergency Medical Services (EMS) in its global customer network, ESO has identified the challenges that our local healthcare settings may be facing for the remainder of 2023.

Staffing shortages were a huge challenge faced by hospitals prior to the pandemic and unfortunately Covid-19 led to many healthcare professionals

Northern Ireland to N The Belfast data com transforming healthc leaving the industry explains Russell Beggs, Vice President of Engineering at ESO Belfast.

“The ongoing aftermath of Covid-19 is still manifesting in burnout amongst hospital workers and many health systems are struggling to maintain the staff they need. This is a trend that’s likely to continue as consequently, high levels of stress, fatigue and burnout fuel staff turnover as professionals actively seek new positions with fewer

stressors, better pay and working conditions.

“ESO is also predicting increased demand for hospital workers, specifically nurses and paramedics, with a particular emphasis on those specialising in geriatric care”, says Russell.

“We are experiencing a transition in global demographics due to rapid population aging and this will mean a

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pressures for the remainder of the 2023.

The next six months will continue to present significant challenges for the healthcare community in Northern Ireland, says Russell.

North America: mpany care Russell Beggs and Jonathan Cummings

much greater requirement for expert care for the elderly. According to the 2021 Census, the demographic of individuals aged 65 and above has grown by nearly 25 percent since 2011 and this is projected to increase, globally and in Northern Ireland.”

ESO also suggests it’s likely

that current economic concerns and pressures are poised to impact hospitals and their systems, as expenses associated with providing services continue to rise due to inflation and challenges with the supply chain. Additionally, hospitals may seek to generate new revenues of income as Northern Ireland healthcare services face funding

“For example, the potential impact on recruitment and retention due to an increased demand for telehealth services. As technology companies provide clinical and nonclinical services, more professionals may leave their traditional settings.

However, this highlights the power of technology which can alleviate the burden on NHS staff with its potential to help ease workloads.

“By harnessing the power of data and technology we can exchange insights and best practices to ensure the highest standard of care is accessible to all patients and pave the way for a brighter future across the hospital ecosystem.”

Whilst we see technology play an increased role in hospital systems and health care generally, ESO predicts this will continue, with digital and even virtual systems having a more significant presence.

Telemedicine is also here to stay with the role of wearable tech growing within the emergency services, as on-theground support teams start to access important information including incident location and patient vitals.

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Like all sectors, the shift to digital first and rise of cyber-attacks is a growing threat in healthcare with consequences including data breaches and compromised sensitive patient information which can often lead to financial losses, reputational damages, and potential harm to patients. In recognition of the growing threat, ESO established a new cybersecurity hub at its Belfast office creating over 30 new tech roles.

Jonathan Cummings, Chief Information Security Officer, based at ESO Belfast said: “Since our arrival to Northern Ireland in 2019, the business has grown exponentially, and Belfast has become an integral part of our global delivery. That is now even more evident as Belfast takes ownership of our cybersecurity function, protecting our customers and ensuring we continue to deliver on our mission of supporting first responders and frontline workers.

“As reliance on connectivity and technology around the world grows, so does our vulnerability to cyberattacks and today’s consequences can include stolen data, loss of networks and involve costly recovery efforts. We operate on the principles of ‘Security-First’, meaning security is a top priority when designing, developing, and deploying any system or application - to mitigate risk and ensure our customers remain confident in what we do.”

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How data plays a role in Fintech CME’s Director of Software Engineering, Roger Moore, reminisces over technologies that have impacted the sector and how data will be adopted to transform the industry q At what stage does Data officially become termed as

Big Data?

There are various measures of what constitutes 'Big Data' at a particular company. Big Data, at its core, is a collection of data from a mixture of sources. One of the best ways to explain this is using the 3 V's, Volume, Velocity and Variety.

Volume accounts for the amount of data generated from multiple sources and saved within your organisation. Velocity measures the speed of data generation, whether that be realtime or in batch or micro-batch. Variety is concerned with the different types of data that is created and processed. This can take the form of structured, semi-structured or unstructured data. All data generated by an organisation has the potential to be useful to someone and the ability to gather and analyse this data is critical to the organisation's ability to make decisions based on what is happening within their company and their wider business domain.

q Big data is a combination of structured, semi-

structured and unstructured data – how do these definitions typically apply in the Fintech sector?

Fintech generates a lot of data. The vast majority of financial data is structured data from things such as trades or market data generated from the various markets. This is structured in predefined formats that make it understandable between different institutions and customers. It allows applications to easily consume and work with the data.

Semi-Structured data encompasses data that does not fit into a relational database model but still has tags that describe the data contained. This can be things like emails, that tag things like sender, receiver, subject, or data from websites that come in a format like JSON. There is information on what the data is but the contents can vary greatly.

Unstructured data can take the form of video, text voice messages and social media posts. One of the big uses of combining the different types of data in Fintech is fraud protection. The ability to understand what is happening in markets and identify trends and unusual activity allows

financial services to manage the markets more effectively. It also enables companies to understand their customers better and create products that help customers and deliver the tools and features they want. Companies that are good at this can be seen to stay ahead of the curve in providing useful services to their customers.

q What are the most challenging and rewarding aspects

of leading a team of over 70 engineers?

The most rewarding aspect of managing multiple teams is watching the success of the teams. That might sound obvious, but what success looks like for each team will be different. The obvious success of delivering stable software to the business is a given, but more rewarding across multiple teams is the success of the individuals within the teams in learning new things and progressing through their careers.

Watching the teams maturing with complementary skills and personalities, growing together and enjoying the work they are doing gives me great satisfaction. Each team will be at their own point in that journey and will be structured slightly differently from the team beside them. Ensuring that every team has what they need to grow and for each individual on those teams to have the ability and opportunity to learn, and progress in their careers is hugely rewarding.

q Over the last two decades what have been the most transformational technologies to have impacted Fintech?

Two decades is a long time in technology. I’m showing my age as I have been in the industry that long and have seen a lot of change. When I started, a lot of financial companies were still running software on mainframes! In the last 20 years, we have moved from there to Unix and Linux servers, to server virtualization and progression of that into on-demand cloud infrastructure. The evolution of cloud computing from a beta AWS in 2002, combined with increasingly cheap storage and lower-cost computing power, propelled the data space forward as more and more data was collected, processed and put to use. With the volume of data generated yearly predicted to be around 175 Zettabytes by 2025, the value in the data

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allows customers to train their models to make better decisions for their business.

Our vast historical data stores allow our engineers to build intelligent data quality models to improve the data we serve to our internal and external customers, allowing us to build new and more advanced data analytic products The continued advances in AI and ML, combined with data, will open further avenues of growth, quality and customer service for many financial companies.

q What would be the best advice you would give to anyone just starting off their career in a Fintech company?

has an immense value.

Sitting on top of this infrastructure is the software to organise all this data. From relational Databases to NoSQL, to building Data lakes, data fabrics and data meshes, the ability to effectively store, access and query these massive amounts of data has evolved as well. With the capability to now store massive amounts of data in effective data structures, ML and AI are coming to the forefront in enabling the enhanced analytics of these datasets to give a much deeper understanding of the data and the ability to make better decisions using the

data. Something that would take humans an immense amount of time.

and the coming together of these with the advent of AI and ML.

In the financial space, the collection, monitoring and usage of this data is critical in providing good services to customers and maintaining well-functioning and well-regulated markets.

Financial services continue to build better connected and informed services for customers that rely on data to provide better products based on customer needs and wants. None of this would have been possible without the evolution of computing storage and computing, the evolution of data stores on top of this,

Here at CME Group, we have entered into a 10year partnership with Google that will transform derivatives markets by expanding access and creating efficiencies that will benefit market users. We are working with Google to utilise their 20+ years of AI and ML experience to gain greater insights into our own business and evolve the whole financial services sector. ML is helping us better understand how our customers are using our services and our decades of historical market data

Fintech is a great place to work. There is a lot of innovation in the financial space and evolution of companies that have a rich history. CME Group is over 150 years old and is one of the first financial exchanges to announce a partnership to move the entire company into the cloud. It is a great place to learn technology and good practice in software development.

There is lots of opportunity to learn, so if you are just starting out, try different things in the business to find the area you enjoy the most. Most financial companies have many different technology teams so there is opportunity to try new things and build your knowledge across multiple domains. This all leads to great experience and builds you into a well-rounded technologist.

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Big data, big opportunity, big challenge David Collins, CEO of First Derivative, gives his take on the future potential of data

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he use of data to drive and augment decision-making has been with us a long time but this new paradigm of big data is delivering huge quantities of data with far greater granularity, far greater frequency and across far more factors. It can make a huge difference to any business that can learn to use this flow of data to optimise costs, spot market opportunities, price dynamically or react faster than a competitor.

The trick is getting to that point as the pathway contains some separate challenges all with different resolutions. Firstly, you need to collect your data, if you are dealing with IOT devices this has one set of challenges, if you are dealing with processed business data there is another. Of course, you will also want to enhance all of that with structured and or unstructured data from related events such as the weather, news, social media or price data. All of this will require a time series database as the timeline is important.

Processed business data has its own challenges, it needs to be clean to be useful and you really need to know the sources or the data lineage.

In complex organisations,

As indicated, we need continuous feedback loops to refine and improve the data science and algorithms. Going back to the pump example, the scenario might be entirely acceptable if the pump is performing a particular task within a particular time frame, that kind of contextual narrative helps to define better detection, the reduction of false positives but to build it into the algorithm will require more data sources.

David Collins

data is often taken and processed into an output that then may further be aggregated. Understanding what data you are working with is critical.

The next big challenge is what to do with it and how to make sense of it.

This is where data science comes in, the data sets and their relationships need to be analysed and a data model constructed. The key indicators in the data are often buried within interrelated triggers. For example: pump A is running hot but by itself it’s not a significant event but if the oil pressure is low and other factors are present then it might indicate imminent catastrophic failure. The data scientist team finds these relationships and continuously refines them over time. This is not a

one-off event, you can do enough to get you going but to derive greater value you need to divert the budget to ongoing data science.

Once you know the factors you are looking for, you need the data science team to build the algorithms to constantly monitor the data flows in real-time but what happens when you hit a trigger? Do you want an automated response or alerts to key operatives?

If you are going to alert someone, how are you going to do it? It needs to be effective and timely and bearing in mind that this data might be being delivered to someone at a desk but equally someone out in the field wearing a hard hat and gloves. Making this delivery or decisioning mechanism effective is very important.

To make all of this real, the example with the pump is not fictitious, a few years ago we built pump monitoring analysis for a client. The project had the good fortune of paying for itself within two months as it predicted potential major plant failure that was caught in time and brought back online quickly with simple routine maintenance. The plant engineers acknowledged that the equipment would have failed spectacularly had it been allowed to continue.

All of this also opens up AI, without the right data sources, modelling and algorithms then the ability to apply AI is severely limited. Big data feels a little like the early days of the technology boom, we gradually had to dedicate more resources to it but the value derived was huge.

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We’re Hiring!

Student Placement Opportunities - 2024/25 Positions available in: Software Engineering IT Service Desk User Experience Product Management

Apply today!

Closing date 29th October

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From cutting-edge technology and high-value exports to skilled apprenticeships and significant investments, ADS sectors are vital to Northern Ireland’s growth and the region’s thriving technology ecosystem that hums with innovation

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DS is the UK trade association with more than 1,200 member organisations from across the aerospace, defence, security, and space sectors. ADS members in Northern Ireland make a key contribution to the technology ecosystem through exciting work with big data and / or unstructured data and ADS itself is seeking to continue to grow its activity in the cyber and digital spaces.

With Big Data Belfast taking place in October, we hand over to Belfast-based ADS member, Datactics, to share their unique thoughts on access to data, the exponential growth of ChatGPT, the risks and what can be done to ensure the role of humans and the continuation of a thriving Northern Ireland technology ecosystem.

With OpenAI’s launch of ChatGPT, the wider world was suddenly introduced to the idea that interacting with data in our own, natural, language would make it incredibly easy to perform complex tasks.

Want a recipe for whatever’s left over in your fridge? Just ask ChatGPT! Want it in the style of Shakespeare? Shall I compare thee to a summer’s quiche? So far, so fun.

Dig deeper, and you can create a Python script from plain text to merge duplicated customer records, or scrub data in SQL without having to code! The capabilities of Generative Pre-trained Transformers such as ChatGPT, one of many such LLMs, immediately get the non-technical among us excited as to the possibilities.

FirstUp ann Largeplans language mo to exp (LLMs) in big data: their workfo

Democratising acce data, or a new Wild Matt Flenley, Head of Marketing, Datactics

odels

ess to d West?

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Underneath the benign exterior of a friendly text box, patiently waiting for a question, lies a complex model which most people will not dig into. It’s in this model where the genius and the risks lie side by side, and like much in this AI-augmented world, make it very hard to distinguish between truth and falsehood.

On launch, ChatGPT was able to be universally useful to anyone. Business executives can craft strategic plans; technical writers can define a whitepaper structure; children in school can create movie scripts for their favourite superhero characters. And would-be poetic cooks can avail of rhyming recipes for their poetic cook books.

By exploring the genius, we can expose the risk, and use our human intellect to examine appropriate ways of controlling or eliminating the risks accordingly. For starters, there are plenty of ways to evaluate the health of the information the models are trained on, and learn from, and test the data, providing explainability for how and why the model made its decisions. Having a human-in-the-loop is still essential to detect and mitigate against the convincing hallucinations that these models may output.

What goes into LLMs?

Why is ChatGPT so popular?

ChatGPT isn’t actually the first of its kind, having been preceded by a few innovations in Generative AI that were capable of winning games against humans, or learning them quickly without being taught the rules. It’s the same idea that goes into rule suggestion engines: defining a set of rules based on experience of the data itself. However, these innovations only really focused on specific use cases, specific games; a subset of human society.

LLMs rely on vast training datasets: think the whole of the internet and everything that has been written, drawn, programmed over time.

These models are taught to learn from this data which in turn allows them to interpret and generate human-like responses in text. Responses are checked using a validation model, known as ‘reinforcement learning’, based on human feedback. The genius of this approach is self-evident, in that computing power to assess huge amounts of data and identify likely responses is the perfect task for computers; but the risk sits alongside it because it all depends on what data is used, how consistent or accurate the answers are, and what they’re used for.

What are the risks?

Right now, there is no global regulation governing which data should be used at this part of the process. Only very recently has the EU legislated on unacceptable uses of LLMs to cover things like performing social scoring, or the value of a person to society. This is legislation which is focused on the now

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– not at what AI will become and as we have seen it is moving and merging at breakneck speed.

In addition, the ease with which the information from a GPT interface can be presented, in friendly chatty language, can mislead the user into thinking that LLMs are ‘fact engines’ which offer undeniable truth. The way they present responses as highly plausible answers, without any view as to what is true, can make it confusing for the reader who might think they can accept answers at face value.

What can be done?

It’s in the subjective space that human oversight is so necessary, in the quality of data being used, the responses being provided

by LLMs, alongside the explainability of the model (that is, why a certain response was provided), and the overall ethical position of the use of the LLM. Ensuring the role of humans in the loop has been a mainstay of Machine Learning development at Datactics, but it shouldn’t be left to software firms to selflegislate their approaches to training data, models, and explainability. The prospects of faster drug research, better medical diagnoses and – yes – poetic recipes are all tremendously exciting.

The low barrier to entry for LLMs, with their universal appeal across ages and nationalities, makes it even more pressing to ensure careful stewardship through consistent regulation.

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Catherine Doyle

The Annual Dell Technologies Forum 2023 Sync NI caught up with Catherine Doyle, Managing Director of Dell Ireland, to talk about the Forum and the latest developments in technology

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he Dell Technologies Forum took place in Dublin on 26th September and showcased how new technologies can be harnessed to advance sustainability, unlock growth, maintain competitiveness and unleash the power of innovation for businesses across Northern Ireland.

embrace innovation are best placed to grow and compete in a global marketplace.

q The annual Dell Forum conference had a great line up

From Generative AI helping organisations to transform data into intelligent applications to Edge Computing accelerating the shift to digital healthcare and smart manufacturing, emerging technologies are reshaping how we work and do business.

of speakers. What was the key message from the event?

In an environment of constant change and transformation, it’s never been more important for businesses and organisations across Ireland to innovate at speed. Organisations that

The Dell Technologies Forum placed an important spotlight on the technologies and strategies that can unlock the power of innovation in the months and years ahead.

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q Innovation is one of the key themes of this year’s Dell Technologies Forum. Are businesses and organisations on this island putting enough emphasis on innovation?

Dell Technologies rolled out our Innovation Index this year and it's one of the key areas that we talked about at the conference. It's proven that in times of change, leaders in innovation tend to adopt new technologies and adapt much faster than laggards. It's interesting that when surveyed 78% of businesses see themselves as innovators on a dayto-day basis, but in reality, only 6% are actually in that leadership category. I think this is something companies need to be aware of and focus on making sure they really think about this when developing their strategy.

One of Dell’s core capabilities is the ability to help customers to focus on the right areas and figure out where they can really drive an outcome for their business. At this year’s Dell Technologies Forum, we focused on actual examples of how customers are harnessing new technologies to drive efficiencies and growth within their organisation.

q Looking back over a 15-year career working for Dell prior to becoming Managing Director for Ireland, what do you consider to have been the key technology milestones for the business during this time?

Technology has always

evolved at pace. From a technology point of view, I think one of the key areas that was most definitive was when it became more people focused. In the past technology tended to be quite back-end applicationfocused but that all changed once it became about enabling innovation and enabling people to act for their companies and drive that outcome.

At Dell Technologies, our core mission as a team is to create technologies that drive human progress.

We are among the world’s leading technology companies helping to use emerging technologies to drive business success and help solve societal challenges. From hybrid cloud solutions to highperformance computing and 5G, our team is using technology to transform ideas into innovation at speed.

q Conference delegates

also got to hear from global industry leaders experts across a wide area of topics including AI, IoT, cloud computing and cybersecurity. What emerging technologies do you think will bring the most radical change for businesses in Northern Ireland?

Artificial Intelligence is unlocking new opportunities for businesses in Northern Ireland and across the world. And although it is one of the most talked about technologies at the moment, it’s probably the least understood.

The real opportunity is making AI enterprise-ready and leveraging the power of data to supercharge innovation within an organisation. Leaders need to understand how AI can transform how they do business and how they're going to use it for the greater good of their company.

I think the next one that would go along with that would be cybersecurity.

Digital transformation is well underway for most companies and hybrid cloud practices have become the norm. But companies need to secure themselves to ensure that their core information and intellectual property is protected. Cyber security and resiliency is becoming a key area for our customers.

If we look also at 5G and how it's going to develop in terms of digital cities and autonomous driving, it's going to really affect everybody in terms of how we actually operate in the future. It will help to enable the roll-out of digital healthcare and the evolution of Industry 4.0.

q AI has been dominating the headlines over the last 12 months. What are the potential impacts of AI from a business and societal point of view?

For hundreds of years the human-machine relationship has been clearly defined.

Machines have been doing mechanical tasks and people have been doing the thinking and decision making. But over the past few years,

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algorithms and data have given us the tools to start to delegate decision-making tasks to machines.

That is a profound change, and it will touch almost every aspect of industry around the world. IDC estimates that by 2025, 88% of the servers used for AI workloads deployed at the edge will be used for inferencing. Given this rapid transformation, AI is now key to unlocking value within data and it is becoming one of the most important tools for businesses of all sizes.

q For a school leaver

or graduate just starting out on their journey and hoping to forge a successful career in technology what important piece of advice would you offer?

The most important advice I would give to anyone is to be open to feedback and mentorship. Be open to being coachable and open to listening to new ideas is a huge learning for all of us really. There is so much opportunity to learn from everybody around you so it’s really important to just be open to that.

It is also critical to take time to invest in yourself. We need to be constantly evolving emotionally, academically and professionally. The technology sector is ever-changing and new ideas and concepts are always popping up. It’s also stimulating to constantly challenge yourself to learn.

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PA Consulting announce investment in new roles Dr Gianluca Barletta, Global Head of Data Science at PA Consulting, discusses their plans to establish a Data Science team in Belfast q Can you tell us about the Data Science team within PA, and why you decided to bring some of these roles to Belfast?

Data Science is a global capability at PA. We have a strong presence in the UK, Nordics, the Netherlands and the US. We work across what we define as the life cycle of data. In fact, even our name, Data Science, really refers to the science of data, encompassing all of its phases. So, we have a group that works around the more foundational aspects of data, such as strategy, governance, and management.

We also have a group that looks more at the data engineering aspect, especially in relation to the move to cloud, including multi-cloud environments.

Thirdly, we have advanced data analytics which looks at the most advanced techniques to actually gather insights from data and that includes all our expertise in artificial intelligence and machine learning.

Belfast is home to some of the most talented data scientists and digital minds in the UK. At PA we have a

vibrant, brilliant, and ever-growing Digital team in Belfast, so investing in our team in Northern Ireland by adding Data Science talent seems like a perfect match, and one of strategic significance for PA. I am very excited by this prospect, and I look forward to welcoming some amazing data experts to our offices very soon.

q What makes PA Consulting’s approach Data and AI different to other organisations in this sector?

Turning client problems into opportunities is really what gets us out of bed in the morning. It's our main goal. Our mission is to solve our clients’ most difficult problems using data. AI, in particular, is central to the strategy.

The importance of AI is absolutely omni pervasive. And it's not just because it's influencing our own lives, but also because it poses questions around how organisations reinterpret their data strategy. For instance, how do you engage with the cloud providers to ensure that you can leverage cloud to scale up AI initiatives fast.

Therefore, we are working on AI with

a two-pronged approach. On the one hand, we look at the opportunities coming from AI. We identify use cases that would deliver the biggest success for their organisation and create detailed business cases to support that.

We would help them experiment and prototype solutions, with architectures and tooling that are ready to scale up.

But equally, we make our clients conscious that they want to go across the so-called, ‘Valley of Death’, where

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expertise in consumer goods, business intelligence, data analytics, AI and machine learning, digital, operational resilience and global supply chains.

In the space of a few weeks, we created a dashboard with the ability to forecast the spread of COVID-19 in such a way that Unilever could plan its production lines and plants and minimise the exposure of its employees to highrisk environments. We aggregated, normalised, and validated over 250,000 data points daily, presented using an automated and dynamic dashboard, and we managed to achieve 80% accuracy with a sevenday forecast of Covid-19 trends at a local level and 75% accuracy on a 30-day forecast, This is a project that PA is extremely proud of.

q PA Consulting has invested heavily in a Belfast Digital Hub, what are the plans for the next 12 months?

Dr Gianluca Barletta

proof of concepts, proof of values or MVPs (minimum viable products) fail to scale up to production. To avoid that, we use what we call the data foundational approach, which looks at the foundations that you need to have in place in order to be able to productionise AI, in order to scale it up.

In most cases, failure to scale up is not due to having

selected the wrong use case but not having solid data foundations in place.

q What sort of projects

has PA Consulting delivered with this approach that have made significant business and societal impacts?

We have many examples coming from our work with the NHS on the Ventilator

project or NHS Hospitals, but one that made a great impact in a very limited space of time is our work with Unilever. The global consumer goods brand wanted to guarantee a certain level of production during COVID-19 whilst wanting to ensure the well-being of each of their employees. PA set out to help Unilever by combining

We’re incredibly proud of our team in Belfast and the impact they have across the work we do for our clients.

We have plans into next year and beyond to continue the expansion across all aspects of our digital capabilities – design, engineering, data science and cyber security.

Over the next 12 months we want to be able to create more career opportunities for people to work in an award-winning organisation which has a focus on digital technology, to help build a positive human future

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Changing the world with future-driven Fintech Engineering manager, Cavan Fyans, explains how Apex Fintech Solutions UK are assisting businesses to make the most of data and AI q For those who are unaware of Apex Fintech Solutions, can you give us an insight into the history of the business and the services it provides?

Apex Fintech Solutions is a fintech powerhouse enabling seamless access and frictionless investing. Apex’s omnisuite of scalable solutions fuel innovation and evolution for hundreds of today’s market leaders, challengers, change makers, and visionaries. The Company’s digital ecosystem creates an environment where clients with the biggest ideas are empowered to change the world. Apex works to ensure our clients succeed on the frontlines of the industry via bespoke custody & clearing, advisory, institutional, digital assets, and SaaS solutions through its Apex Clearing™, Apex Advisor Solutions™, Apex Silver™, and Apex CODA Markets™ brands.

q Big Data is often defined in terms of Volume, Variety, Veracity, and Velocity – how does Apex optimize these features for its clients in the real world?

At Apex, the data layer is not just about the challenges

that come with bigness; it's about managing the data, infrastructure, and services that make it easier and more efficient for our clients to interact with and extract meaningful insights from our diverse data sources. We, the data team, are enablers for them to build value on our data while we ensure tenets like accuracy, speed, and security.

The Apex data platform is relatively new to the cloud data space, and we are moving fast in building out and optimising for the fundamental features of big data while we respond to our client’s data needs. The core of our cloud data platform, built within GCP, operates as a central data lake with a surrounding data mesh architecture for consumption and access. We have both internal (service teams) and external consumers (clients) that pose differing challenges as we must operate both as an internal services team and a client product team.

I say it slightly carefully, but the bread and butter of the big data world are somewhat solved problems (that’s perhaps

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the first two V’s; central storage, distribution, access, etc.). We do have to be attentive to how we architect our central data solutions, but the challenges are more often in the outer layers and how we optimise against the change and movement of data at scale; how we find the right architectures, services, and mediums to drive quality, privacy, security, and efficiency that will deliver fast routes to value for the data products that are built on top of our central data platform.

q Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time – How does AI and Machine learning overcome these problems?

AI and machine learning are pivotal in addressing the challenges posed by big data. These technologies excel in handling large volumes of structured data that have traditionally been difficult to work with at scale. The convergence of structured data, AI/ML, and modern parallel & and distributed computing (… cloud-everything), makes it easy to process and sift through vast amounts of data fast. AI/ML systems and tools are very good at identifying patterns, trends, anomalies, modelling, summarising, etc. — tasks that would be impossible for humans or individual systems to achieve. This advanced technology enables efficient AI/ML-powered automation of big data tasks like data preparation, cleaning, identification, etc.

But, perhaps more importantly than just making us more efficient, these tools also allow us to redefine the ways we can work with data. For example, the way data users can explore or identify data; by leveraging GPT/LLM style tools, we can enable humans to be able to interact, query, and search data in a conversational manner without the necessity for data-query language skills or data catalogue abstractions.

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volume (relatively known) and bursty API usage (relatively unknown) to ensure that we can guarantee healthy data and fast response at the live model.

q What makes Apex an exciting place to work, and what qualities do you look for when building a successful team in Belfast?

Cavan Fyans

This ease-of-use can expand the accessibility and visibility of data, allow more people (different stakeholders) to explore and understand our data, and ultimately understand how to derive value from it.

q Is Cloud and Serverless the

future or is there still a place for traditional data warehouses?

There’s no doubt that the landscape of data storage, processing, and access is undergoing continual transformation.

There’s always going to be some debate between cloud-everything and traditional data warehouse approaches to data platforms. In most cases, there is a use case for everything. Engineers should be looking for the right tools for the job to build value for their client or business, rather than looking for the latest trend for the sake of buzzwords.

At Apex, we are inherently cloud focused. We leverage the efficiency, performance and availability of cloudbased data systems in order to provide the data surface and tools that our consumers require. Our live ML models are a prime example of the performance and scalability requirement that is only possible in the cloud. In order to run these models we have to be able to process the large volumes of activity data used to train the ML models and have high, performant availability of the online feature data (used to feed the live model on request), while also serving the ML models. All of this needs to be able to scale rapidly for both data

At Apex Fintech Solutions, the recent transition to cloud computing and cloud data platforms has opened up exciting new possibilities. We're not bound by years of legacy code or stuck in a traditional way of working. Instead, as a data team, we are building in fresh cloud pastures. We actively encourage our engineers to shape this future, to innovate, adapt, learn, and define as we move forward.

For me this is very exciting. As engineers, we have the scope and autonomy to work closely with the other business verticals and define our path forward. In our data-platform we maintain centralised tooling and services but decentralise data ownership. In this way, our data team are no longer really “data engineers” in the traditional sense. And we’re not really SQL experts — I prefer to define us as cloud engineers who sit next to the data. We’re building cloud services, so we inherently need to be good engineers first, maybe with a data appreciation and focus second.

The qualities I look for in engineers are collaboration, innovation, and adaptability. Engineers who have a product mindset and want to understand the why as well as what and how. For me, these qualities are much more important than specific skills in languages or technologies. In the Apex data team in Belfast, we work concurrently across the breadth of our data platform; cloud (micro)services, analytics engineering, ML Ops and services, APIs and backing services - so there is a lot of scope for different skills, focuses and futures.

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Keith Farley

Q&A with Keith Farley Aflac’s Senior Vice President looks back at his time in Belfast as he returns to the states after four years q Having made Northern Ireland your home over the

last four years, how does it feel to be back living in the US?

It's mixed feelings to be honest, we absolutely loved our time in Northern Ireland. It was our home for four years and as resident tourists, we travelled almost every weekend and got to see so much of the country. We enjoyed a whirlwind lifestyle yet workwise we were of course also starting a new company from scratch – everything was new and everything about our life was different for four years. Now we're going back to somewhere that we know and, naturally, there's comfort in that. One thing that surprised us was how much a place can change in just four years and how much America had changed while we were gone, but also how much we had changed.

It's been a bigger adjustment than I would have thought

because we had adjusted so well to the lifestyle in Northern Ireland. Everything – from the people, the ease of transport and the fact that we could walk everywhere – was amazing.

It’s a full car lifestyle now that we’re back and we have to drive everywhere.

q You made an enormous impact on the NI tech scene, becoming an instantly recognisable personality wherever you went. Was there anyone in the local tech sector that has left a lasting impression on you?

There were so many individuals that really left a huge impression. However, if I start with those I met outside of work and with people I’ve become friends with then I must mention Gary, Stephen and John from Bogart Menswear and the way that they treated us. I also have to mention John from The Belfast Clipper barber and of course my wonderful neighbours from Holywood who left me with so many good

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memories.

From the tech sector, it’s worth mentioning that when Aflac first arrived, several of our major US competitors were already established here and yet I was surprised with just how welcoming and supportive they were.

I would have thought that given these guys were my competitors, they weren’t going to like me or that I’m not going to like them.

Nothing could be further from the truth. Such is the Northern Irish spirit that everybody wants to work together, making sure that we're all doing what's right for the community.

q It was an incredible

achievement that during lockdown, you were able to establish Aflac in Belfast and build a team of over 140/150 people.

What's the secret to the success and what lessons did you learn?

I think the secret to the success of what we did was giving our employees a voice in almost every decision that we made. We wanted this to be a company that they were starting and creating and not something that they were joining that had been predetermined in the US. We wanted the first 30 to 50 employees to be the authors of the company, the next 50 to 100 to be editors of the company and we never wanted to get to the point where someone would be just a ‘reader’. We've since been editing and re-editing everything at Aflac Northern Ireland, ensuring all our valuable employees have a

decision in everything we do, whether that’s where our office would be, it’s layout and furniture, to the type of work we do and to the charities we support. For me, the secret sauce was about our employees really directing the company and deciding themselves what kind of company we would be.

q Northern Ireland has

established itself as a technology and innovation hub for numerous US companies. What's the attraction and how did reality compare with your expectations?

Northern Ireland was a place that truly wanted our company here. We felt that there was a genuine desire for us to be here from the government, the universities and even from the other companies in the city and region, which again was a welcome surprise. The main attraction, I think, was that Northern Ireland wanted us and that really helped us want Northern Ireland.

We looked at 15 different cities before landing in Belfast and some places would have been ‘okay’ with having us, but we really felt that there was a genuine and passionate desire from Northern Ireland in wanting us to come. We also knew that if we did make the decision to locate in Belfast, everyone from the government, local business organisations and through to the universities would do everything in their power to ensure we were welcome and successful.

What surprised me the most was the talent. We had heard that there was really good talent available but it’s not until you see it in action that you say, “Wow, this is something that I can put my hands on and say this is different, this is better than what I've seen". Probably the biggest surprise was when we started producing results and just how strong those results were compared to other parts of the world we had looked at. Living in Northern Ireland, I also started to see why the talent was so strong. My kids were in the school local system, and I saw how challenging the school system is and how selective the school system can be. It really drives kids to want to work hard to succeed.

q Aflac in Belfast is in great shape and is now led by a very experienced and popular Mark McCormack.

Are you able to share what if any advice you gave to mark before handing over the baton?

Mark was the first employee and a co-founder of Aflac in Northern Ireland and during those four years, Mark was part of every decision that was made so we knew there would be good continuity. During the early part of our journey, or what Mark jokingly refers to as the ‘Farley years’, I said to him ‘’as you move into the McCormack years, you need to make it your own place, it needs to have your fingerprint on it and your style’’. Until recently, the company had both of our fingerprints on it but now

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I'm back in the US. The main advice I gave Mark was to not just run the company that we built but to relaunch it. It should feel that there is some continuity of course but it should also feel different too, with a new style that people will know and feel.

q What would you personally like to take from Belfast and introduce to Columbus, Georgia? And conversely, what would you like to introduce from Columbus into Belfast?

As well as certain food things, there are some cultural nuances that I really liked and will miss.

Obviously, there are small things like Cheese & Onion Tayto crisps and Cadbury chocolate which we don’t have in the US, and of course, there’s the famous Ulster Fry…but that said, I still prefer streaky American bacon!

I also love how people in Northern Ireland often let someone into traffic and are ‘thanked’ for the gesture by a flash of the hazard lights.

It's such a nice thing and I just think that it's a great, warm nonverbal cue of how we communicate with strangers around us that are in our lives because of the proximity they have to us.

That spirit of generosity that people have in Northern Ireland is something I would love to bring back to the US and to Columbus. People really do want to take care of each other, and I've seen it and felt it firsthand.

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Mark McCormack and Keith Farley

I would say, though, that some of the exciting sports culture in America is something that I missed most when I was away from home. I love US sports, especially the large stadiums filled with over 100,000 people which are loud, but they really bring communities and people together. You have that in Northern Ireland too, although there's also maybe a bit of a division in some sporting circles.

However, hockey and the Belfast Giants seem to do something that everybody can rally around.

In terms of food, there's a couple of American restaurants such as Waffle House and Chick-fil-A that we missed and would love for the folks in Northern Ireland to get to experience

them, but honestly, there's not a whole lot I would swap in either country. I like the personality that each of them has on their own – it’s nice that they’re known for what they’re known for.

q What's the next chapter for you and what would you like to see in the future for Aflac Northern Ireland?

Moving from the IT and cybersecurity side onto the business side, I am now the consumer of all the work that's being undertaken in Northern Ireland which is wonderful for the local team and for me. It's particularly great for me because I personally know every member of the team that's working on the technology in my business, and I trust them. There’s a lot of comfort there. For the local

teams, hopefully, there's greater comfort in knowing that that their direct customer is someone who confidently believes in their abilities and skill. After all, I’ve been working with them for years!

What's next for Northern Ireland? What I'd like to see for Aflac Northern Ireland is that it continues to expand and increase its influence within the wider company while being core to the company and the strategic decisions taken globally.

within Northern Ireland, but it’s a great place full of wonderful people. There are too many to mention by name, but I have a love for the people of Belfast and Northern Ireland, people with a great – and often dark – sense of humour that I find so hilarious. Generally, everyone is kind, and they really want to help you out.

That’s something I have loved showing off when colleagues, friends or family came to visit.

most about Northern Ireland?

That’s an easy question! It is of course the people, who are wonderful.

I’ve loved taking family and friends out and about and just letting them see the community in action here whether that’s in a restaurant, a pub, or simply shopping to interact with local folks.

I know there's a lot of focus sometimes on the divisions

It’s always been a great experience.

q What will you miss

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Helping AI help us meet today’s biggest challenges AI has the potential to help us solve many of today’s grand-scale challenges, writes Rachel Steenson FBCS, Vice-Chair of BCS Council. But, we need to ensure AI – and the data it relies on – is managed professionally

W

hen ChatGPT burst onto the scene in late 2022, AI became the talk of the town. If the headlines were to be believed, suddenly and from seemingly nowhere, had come a technology that could do anything.

AI could write poetry, pen corporate reports, generate recipes and more.

individuals and society? Can we trust AI? Will AIs take our jobs?

These concerns have led some to call for a pause in AI development: we should stop developing and deploying until we’re sure AI can be trusted.

BCS and its members feel differently. We believe we should help AI grow responsibly. We believe registration, professional standards and responsible computing will form the basis of an approach to engaging with AI safely.

It’s also important that AI and data professionals have places to meet, share, learn and network, including events such as Big Data Belfast.

The truth about AI is quite different. Artificial intelligence is a family of technologies, most of which have been the focus of academic and commercial research for decades.

During that time, AI has had summers, like the one we’re experiencing now, but it’s also had its winters — times when it fell from favour.

Today’s AI summer is burning hot thanks, in part, to cloud computing and its ready abundance of processing power and storage. We’re also living in the age of big data: organisations hungrily build up terra-, peta- and exabyte portraits of their customers' tastes, preferences, locations and purchases.

These datasets are so big, it’s impossible for a human to find value in them, hence

Rachel Steenson

the need for AI. We’re fortunate that AI is reaching maturity right now. With the world facing grand challenges like ageing populations, cancer, climate change and the need for decarbonisation, AI will be an invaluable tool in the hands of scientists.

But don’t be fooled. AI

isn’t fully grown up yet and is prone to stumbles and errors. If the data we feed them contains bias, then AIs will act based on those biases and the AIs themselves are so complex that it’s hard to explain how they reached their conclusions. How do we ensure what AIs are recommending is actually correct and good for

Finally, we also believe in diversity. For AI to fulfil its potential and help us tackle those grand-scale challenges, we need engineers and designers with different backgrounds and lived experiences. We need them to bring their unique insights to the table, the keyboard and the kanban board.

To find out more about BCS, visit www.bcs.org.

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The future is

open with flexible study that means you can learn while you earn

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