Graham Baitson Blog

Everything is Learnable: Step by Step

Tue, 02 Jun 2026 16:40:44 GMT

Last year, I had the opportunity to speak at StartUp Ballymun: Innovation in Action, a community event celebrating local entrepreneurship and innovation. With this year’s event coming up on June 10th, I’ve been reflecting on some of the lessons I shared that night.

As the audience included people from very different industries and backgrounds, the talk itself wasn’t really about technology or startups specifically, it was more about recognising that most careers are built step by step over time and that a lot of things that initially feel unfamiliar or intimidating eventually become learnable through curiosity, repetition, consistency, and experience..

Navigate Uncertainty

Growing up, I learned early that trying to fit into every environment rarely adds much value. People who think differently often approach problems differently, and that becomes increasingly important later in life because careers, leadership, entrepreneurship, and even life in general are rarely predictable. Very little is ever fully certain, so learning how to operate without always having every answer upfront becomes an important skill.

Be Resourceful

When I was finishing school, I spent a huge amount of time researching different potential courses and career paths. That eventually led me toward organisations like BITE and DCU Access, which provided information and support on grants and scholarships, unlocking many additional opportunities. But looking back, the most valuable thing I gained from that experience was not simply access to education, it was learning how to navigate uncertainty through research, persistence, and initiative.

Learning how to ask the right questions, identify opportunities, build a network, and find pathways forward when things are unclear, become incredibly valuable skills later in life. Resourcefulness is often just as important as knowledge and skills.

Believe in Yourself

My first role out of college involved building a virtual reality medical simulator for surgical training. At the time, it felt incredibly advanced and intimidating. But over time, I realised that most complex things become manageable once you break them down into smaller building blocks and focus on learning gradually over time.

That mindset changed how I approached challenges afterwards. Over the years, I accumulated skills, experiences, and perspectives that helped me navigate problem-solving, emerging technology, leadership, business, and the many different challenges that come with building and growing things. None of it happened overnight.

Confidence is rarely a straight line either. I experienced that through sports where, at different points, I represented Ireland playing pool. Like most competitive environments, confidence fluctuates massively depending on preparation, results, momentum, and mindset. But one thing I learned in both sport and business is that confidence tends to grow through preparation, consistency, and action, not through overthinking every step beforehand.

Learn the Fundamentals

Some of the most valuable years of my career were also the years where I learned the core fundamentals properly. I spent years building systems, solving problems, and learning how businesses and people actually operate in practice. At the time, some of those experiences may not have looked particularly exciting from the outside, but they created the foundation that made it much easier to adapt to new industries, technologies, leadership responsibilities, and business challenges as opportunities evolved over time.

Fundamentals have a way of quietly compounding in the background. The stronger your foundation, the easier it becomes to build confidence, adapt to change, and tackle increasingly complex challenges later.

Be in the Room

Looking back, many opportunities in my career came from continuously putting myself into environments where I could challenge myself, learn, contribute, and build relationships. Over the years, I have worked within small teams and global teams, startups and multinationals, across many different industries, and have had opportunities to travel, build global teams, and work on interesting projects involving emerging technology such as location-tracking, wearable technology, and AI. Some of that came from curiosity, some came from intentional career decisions, and some simply came from being present when opportunities appeared.

While I do believe in being strategic about your career and deliberately aiming to build the right skills and experiences over time, strategy only works if you also put yourself into rooms where learning, relationships, and opportunities can actually happen. You do not need to know everything before entering those rooms, you just need to intentionally place yourself in these environments with a willingness to contribute, learn, and adapt.

Surround Yourself With Good People

This might be the most important lesson of all. Almost every major opportunity in my career came through people. Former colleagues became mentors, conversations became partnerships, and networking events led to opportunities years later. Many people I worked with throughout my career have also become genuine long-term friends. We stay in touch, support each other, take an interest in what each other are building, and help each other where we can. Over time, all these relationships become incredibly valuable, both professionally and personally. The people around you influence your standards, your thinking, your confidence, and sometimes even the direction of your life more than you realise at the time.

Take Calculated Chances

For me, entrepreneurship is not about randomly taking risks. It’s about recognising opportunities where technology, industry knowledge, commercial understanding, relationships, and experience have converged in a meaningful way.

Building a company forces you to combine strategic thinking with adaptability every single day. You need vision, but also need execution. You need confidence, but also humility. You need to move quickly while still being thoughtful about decisions. And none of it happens alone. Surrounding yourself with a strong team of people you trust and can rely on becomes one of the most important parts of building anything meaningful.

Leverage Technology

Technology should feel empowering rather than intimidating, especially for SMEs and non-technical businesses. Digital tools, automation, and AI are lowering the barriers to learning, building, analysing, creating, and competing. You do not need to be a software engineer to benefit from these technologies. In many cases, the real opportunity is not replacing people, but allowing people to spend less time on repetitive manual tasks and more time on analysis, creativity, and decision-making. The businesses and individuals who benefit most will likely be the ones who learn how to combine human strengths with technology effectively, using technology to enhance human capability rather than replacing the human element entirely.

Final Thoughts

The final slide in my talk was simply:

Get Comfortable Being Uncomfortable
Be Resourceful
Believe in Yourself
Learn the Fundamentals
Be in the Room
Surround Yourself with Good People
Take Calculated Chances
Leverage Technology

Looking back, I think most careers are built through curiosity, consistency, adaptability, relationships, and a willingness to keep learning over long periods of time. Modern careers are rarely linear anymore. Very few people have everything figured out in advance. Most are simply learning, adjusting, improving, and building as they go.

And maybe that’s the real point. You do not need to have every answer before you begin. You just need to stay curious enough to keep learning.

It was a privilege to share the stage alongside Bobby Healy from Manna Air Delivery, Lucie Cunningham from THE HomeShare, Edizemi - Onilenla, Sinead Ryan from Little Fitness, and Eileen McHugh from Hair Together Salon & Academy, and hear the different perspectives and experiences each person brought to the discussion.

Beyond Buzzwords: One Year Later

Tue, 26 May 2026 15:32:36 GMT

June last year, I spoke at the BNI Ireland inaugural National Conference on a panel titled “Beyond Buzzwords: What AI Actually Means for Your Business.” At the time, AI conversations were everywhere. Every week seemed to bring another prediction about autonomous companies, mass job replacement, or businesses being left in the dust if they didn’t adopt AI immediately. But the conversations happening in the room that day felt very different.

The audience were not AI researchers or technology founders. They were SME owners, operators, consultants, and entrepreneurs trying to understand what any of this actually meant for their business. And their questions were practical. Is AI genuinely useful? Is it all just hype? Do I need technical skills to benefit from it? Where do I even start?

Now, almost a year later, and with the 2026 BNI Ireland National Conference coming up this week (Friday, May 29th), I’ve found myself reflecting on the thoughts I shared that day and how much the AI conversation has evolved in such a short period of time.

The Shift

At the time, many SMEs were still cautiously testing AI. People were experimenting with tools, becoming familiar with prompts, generating content, and figuring out how any of it fit into their day-to-day work. They had curiosity, but also hesitation, and many businesses still viewed AI as something separate from their normal operations.

Over the last year, there’s been a noticeable mindset shift. Businesses have increasingly moved away from asking whether they should use AI, and instead started to identify where AI can genuinely create value for them. That’s a very different conversation.

The focus became less about a shiny new tool and more about operational efficiency. Not replacing entire teams overnight, but removing friction from everyday work. Whether that’s improving response times, summarising meetings, or reducing repetitive admin, it has helped smaller teams move faster and realise true value across practical operational improvements.

In the space of a year, the technology itself has also advanced at an extraordinary pace. Industries moved from prompting and content generation towards integrated systems, workflows, and orchestration. The ability to connect isolated thinking into systems capable of coordinating tasks, conducting research, generating software, and delivering end-to-end services in ways that would have felt ambitious just twelve months ago.

The Human Layer

But with these connected systems, the human element has become more important, not less. Back in 2025, many businesses were casually experimenting with public AI tools without fully considering the implications around data privacy, reliability, or accountability. This conversation has matured considerably over the last year, with businesses now asking much better questions. How do we integrate these tools responsibly? Can we trust the output? How do we verify accuracy for critical workflows?

That shift in mindset is important because AI adoption has moved from being purely a technology conversation towards a more operational and leadership conversation. One thing that became clear is that the businesses benefiting most from AI aren’t necessarily the ones talking about AI the most. They’re the ones quietly integrating it into real workflows, solving genuine problems, and improving how their teams operate one practical improvement at a time.

Even with the growing conversation around orchestration and agentic workflows, the core principle still remains consistent: the real value of AI is not replacing people, but enabling them to focus more of their time on higher-value work.

Final Thoughts

Looking back, I'm glad the focus of the panel leaned more towards the practicalities of AI rather than predictions. In some areas, the technology has evolved far quicker than anticipated, while in others adoption has been slower, more cautious, and more dependant on governance and organisational readiness than many expected.

Interestingly, much of the advice around getting started still holds true. The key is understanding where the real challenges, inefficiencies, and opportunities exist within a business, and identifying where AI can create value and meaningful returns. For some organisations, that may mean starting small, experimenting carefully, and staying hands-on with the output. For others, particularly where AI sits closer to the core value proposition, the opportunity may justify a deeper level of investment from the beginning. That also aligns with the broader shift happening in commercial models around AI. We're starting to see the move away from traditional seat-based pricing towards more usage and value-driven approaches, where understanding the impact of the output increasingly shapes the investment decision itself.

At the same time, the capabilities, creativity, and realism of the technology have advanced to the point where it's becoming increasingly difficult to distinguish between what's real and what's generated. That creates exciting opportunities, but also increases the importance of trust, transparency, and ethical use. And maybe that's why that 'Human Layer' feels more important now than it did a year ago.

Despite all that change, I still think the businesses benefiting most from AI will be the ones that approach it thoughtfully, focus on solving genuine problems, and apply technology in ways that create meaningful value. One year later, it's those fundamentals that still matter more than the buzzwords.

It's an exciting time, and I'm looking forward to seeing how the conversations evolve for the remainder of 2026. As someone who is actively building products and workflows in this space, I'll certainly be keeping a close eye on the next wave of tools, ideas, and systems that continue pushing the boundaries of what's possible.

Until next time. I hope you enjoyed the read. GB

Photos by: Dermot Byrne Photography

The Fascination of Language (Part 2: Lost in Translation)

Mon, 20 Apr 2026 13:03:40 GMT

5 Minute Read – For the lucky ones, language is something we learn early, and over time it becomes second nature. I’ve always been fascinated by people who can speak multiple languages, especially when they can inject their own personality and culture into conversations in other languages.

At the same time, the way we use language is evolving. With AI platforms now processing over 500 million interactions per second (Medium, 2025), parsing messages, predicting intent, and generating responses, language is no longer just human. And yet, we’re still trying to fully understand it ourselves. If anything, as machines build their interpretation, it highlights just how complex language really is.

In the second part of this series (following Who’s Thomas.... And Why is he Doubting? ), I want to explore a few words from other languages that have come into my world. Words that perfectly capture specific feelings, situations, and ideas, yet don’t have a direct English translation. All thoughts, views, and comments are my own..

Augenblick (German)

It almost feels like there is an English word to describe every situation, but every now and again, you come across a word that reminds you that isn’t quite true. A couple of years ago, I attended a virtual mindfulness session by Dr. Lisa Nezneski, where she introduced the German word augenblick, meaning “in the blink of an eye”.

One of the hallmarks of our modern era is pace. It’s relentless, chaotic, and rarely slows down. But within that chaos, there are moments - small, almost invisible moments that carry enormous weight. Moments of change and clarity where something just… clicks. And within those moments, something shifts, direction changes, decisions are made, and opportunities appear.

But with that pace, our expectations also move, especially when it comes to technology. We measure everything from processing speed to response times. Everything is expected to be instant. But not all “instant” moments are equal. Some define direction, some shift thinking, and some change outcomes entirely. And some happen in an instant… In the blink of an eye. Augenblick.

Schmilblick (French)

When I have some downtime, I enjoy going skiing in the French Alps and regularly stay with a French friend of mine and his family. One word I hear quite often in conversation is schmilblick. It was introduced by French humorist Pierre Dac as a made-up, imaginary object. Something people had to describe and figure out. It later became popular through a radio game where contestants had to guess this unknown, almost abstract item by asking questions and gradually building up an understanding of what it could be.

Today, it’s used more loosely, as a placeholder for “thing,” “stuff,” or something you can’t quite define. And there’s something interesting in that when you think about how ideas take shape in technology. In AI especially, things rarely arrive fully formed. But that doesn’t mean they lack direction. There’s usually a clear objective, a strategy, and a set of guardrails in place. From there, it’s about iteration. Refining through conversations, learning from real-world application, and adapting as you go. The end goal might stay the same, but the path evolves over time. And often, it’s that balance between structure and flexibility that turns an early idea into something far more impactful than originally imagined.

In a way, every product, every feature, every idea... starts off as a schmilblick.

Sisu (Finnish)

There are words you see often but don't really stop to think about. Sisu was one of those for me. I’ve regularly walked past the store, but never really looked into what it meant. Until curiosity got the better of me. Sisu isn’t defined by a single word. It’s a combination of resilience, determination, perseverance, and the ability to keep going when things aren’t going your way. Not just when it’s easy, but when it isn’t.

And you see that everywhere. In sport, in music, in business. The things we often label as “overnight success” rarely are. It’s the extra hours no one sees. The setbacks along the way. The consistency when things aren’t working. There’s always more behind the moment than what people see.

And maybe that’s what sisu really is. Not the moment itself. But everything that led up to it.

Hygge (Danish)

Some words don’t describe action, they describe a feeling. Hygge is one of those. I’d heard it mentioned a few times over the years, usually in the context of Danish culture, but it wasn’t until I started paying attention to it that it actually made sense.

It’s that feeling of comfort, warmth, and ease. Sitting around with friends, good food, good conversation. Nothing planned, nothing rushed. Just being present in the moment and enjoying it for what it is. It’s simple, but it stays with you.

And it’s interesting to think about that in the context of where things are heading. We’re building more advanced systems, more automation, more ways for machines to interact with us and with each other. As technology continues to evolve, especially in AI and robotics, there’s a growing focus on making interactions feel more natural, more human. But no matter how far things go, there’s always going to be something in those moments that can’t be replicated.

Because hygge isn’t just about the environment. It’s about the feeling you get from the people in it .

Final Thoughts

When you think about language, it’s easy to focus on words themselves. How they’re formed, translated, or interpreted. But the more interesting part has always been what sits underneath them. Their meaning, context, and experience.

Because language has never just been about communication. It’s about interpretation. And interpretation is shaped by everything from culture, memory, emotion, and timing. That’s why the same words can mean different things to different people, even when they’re technically “the same.”

And this is where it gets interesting with AI. We’re now building systems that don’t just process language, but try to interpret it. To understand intent. To respond in a way that feels relevant in the moment. And in many ways, that’s the challenge. Not just what is being said, but what is actually meant.

Because whether it’s a moment that changes direction in an instant, an idea that starts as something undefined, the persistence behind long-term progress, or the importance of simple human connection, these things don’t translate cleanly. They’re felt more than they’re explained.

Maybe that’s the point. Even as machines get better at understanding language, the most important parts of communication will still be the ones that aren’t fully definable. The parts that depend on context, nuance, and being human. And that’s what makes language so fascinating. Not that we’ve mastered it, but that we’re still figuring out how much more there is to understand.

Until next time. I hope you enjoyed the read. GB

References

Figure Cover. (2025). Linguistics in the Age of AI: Why Language Majors Matter More Than Ever. [online] Available at: https://www.linkedin.com/pulse/linguistics-age-ai-why-language-majors-matter-more-than-syafaat-tprbc . [Accessed 14 April 2026]
Figure 1: Augenblick. StockCake. (2026). Vibrant eye close-up. [online] Available at: https://stockcake.com/i/vibrant-eye-close-up_1327014_953341 . [Accessed 13 April 2026]
Figure 2: Schmilblick. MIT Sloan Management Review. (2017). The Critical Difference Between Complex and Complicated. [online] Available at: https://sloanreview.mit.edu/article/the-critical-difference-between-complex-and-complicated/ . [Accessed 15 April 2026]
Figure 3: Sisu. The Havok Journal. (2024). Why Sisyphus Matters. [online] Available at: https://havokjournal.com/culture/life/why-sisyphus-matters/ . [Accessed 15 April 2026]
Figure 4: Hygge. LuxedDecor. (2026). How to Hygge: 8 Scandinavian Design Lessons. [online] Available at: https://www.luxedecor.com/style-studio/how-to-hygge . [Accessed 15 April 2026]
Medium. (2025). 1.3 Quadrillion Tokens Monthly Just By Google AI and Counting. Available at: https://medium.com/technology-hits/1-3-quadrillion-tokens-just-by-google-ai-and-counting-c1540a37c5d2 . [Accessed 14 April 2026]

The Economics of Flight

Fri, 23 May 2025 13:40:25 GMT

5 Minute Read – The aviation industry is navigating a period of rapid change, shaped by supply chain constraints, geopolitical concerns, and the changing landscape of aircraft leasing and maintenance. These forces reveal an industry in flux yet full of potential.

A Decade of Delays: Aircraft Manufacturing Challenges

With a backlog of 17,000 unfilled aircraft orders (Forbes, 2025), and delays potentially spanning up to a decade, original equipment manufacturers (OEMs) are struggling to meet the demands of a rapidly recovering travel market. Issues like supply chain disruptions, engine durability concerns, and labour shortages are testing the industry’s resilience and ability to meet demand.

Supply chain disruptions

Aviation supply chains remain a significant bottleneck, hampering aircraft production and delivery schedules. Manufacturers like Airbus and Boeing are grappling with shortages of essential components, raw materials, and skilled labour. Last year, Airbus delivered 766 commercial aircraft, just slightly below its target of 770, while Boeing fell far behind, delivering only 348 planes. The shortfall has been attributed to increased regulatory scrutiny and a prolonged strike by factory workers (Business Insider, 2025), challenges of which are forcing both manufacturers and airlines to rethink their strategies for meeting rising demand.

Engine Maintenance and Durability Issues

Modern aircraft engines, while more fuel-efficient and environmentally friendly, are experiencing durability problems that require more frequent maintenance and repairs. Issues like contaminated powdered metals in Pratt & Whitney’s PW1100G engines (Reuters, 2023) and rapidly degrading fan blades in Rolls-Royce’s Trent 1000 engines (The Times, 2024) have led to increased maintenance demands, forcing airlines to ground planes more often than anticipated. As fleets face reliability issues, manufacturers are caught in a balancing act, meeting the demand for new engines while keeping existing ones operational. The result is operational disruptions that manifest as delays, cancellations, and heightened maintenance costs.

Labour Shortages and Production Bottlenecks

The pandemic’s shadow continues to cloud aviation labour markets. Skilled workers who left during the pandemic haven’t returned, and training replacements for the complexity of modern aircraft manufacturing takes time. This gap is slowing production, leaving manufacturers to deal with growing backlogs. Airlines, meanwhile, are keeping older aircraft in service longer to bridge the gap, placing additional strain on maintenance facilities.

A Golden Age for Lessors

Aircraft leasing has become the backbone of aviation. The share of leased aircrafts has skyrocketed from 3.6% in 1980 to over 51% today. For leasing companies, the production delays have opened the door to capitalise on rising demand for mid-life aircraft and lease extensions. Airlines are prioritising profitable routes and extending the lifespan of their fleets, creating opportunities for lessors to secure favourable lease terms and expand their portfolios. This period has reinforced the value of agile and strategic asset management within the leasing sector.

However, the surge in demand for repair and overhaul services has stretched maintenance shops to capacity, driving up turnaround times and costs. Lessors are also adapting to sustainability goals, investing in more fuel-efficient aircraft and exploring ways to stay competitive as the industry transitions toward greener operations. While full of opportunity, the pressures on maintenance, sustainability concerns, and the growing complexity of fleet management are likely to shape the aviation sector's landscape in the years to come.

Geopolitical and Economic Challenges

External geopolitical and economic factors are having a significant influence on aviation, shaping recovery efforts and long-term growth strategies. Three key challenges include geopolitical tensions, rising interest rates, and regional disparities.

Geopolitical Tensions

Trade disputes and political instability have disrupted supply chains and delayed aircraft part deliveries, adding uncertainty to manufacturing timelines. Airlines have also been forced to adjust flight routes to ensure passenger safety, further complicating global operations.

Interest Rate Normalisation

Historically low interest rates helped keep aircraft financing accessible. Interest rates are now expected to stabilise around 4% over the next 12 to 18 months (SMBC Aviation Capital, 2025). This higher rate environment raises the cost of capital for airlines and lessors, increasing financial pressure when purchasing or refinancing fleet assets, and potentially slowing growth and profitability.

Regional Disparities

Aviation’s recovery since COVID-19 has been uneven across regions. While North America and Europe are seeing strong rebounds, some parts of Asia, such as Thailand, are still operating at reduced capacity. Inflationary pressures and lower consumer spending in certain areas add another layer of complexity, making it harder for airlines to navigate their financial and operational challenges.

Sustainability and the Future of Aviation

The aviation industry is under mounting pressure to reduce its carbon footprint. Sustainability has moved to the forefront, with airlines, manufacturers, and lessors investing in greener technologies.

Sustainable Aviation Fuel (SAF)

One major advancement is Sustainable Aviation Fuel (SAF), which offers a significant reduction in carbon emissions by being made from renewable sources like agricultural waste. Industry collaborations, such as the partnership between SMBC Aviation Capital and Trinity College Dublin, are working to make SAF commercially viable and scalable.

Electric Aircraft

Electric aircraft are gaining traction as a solution for short-haul flights, promising even greater emission reductions. However, these technologies are still in development, and the transition to greener fleets presents challenges, especially for lessors managing mid-life and older aircraft that may lose value as airlines embrace newer models. Balancing the economic realities of fleet renewal with the urgency of sustainability will require significant investments, regulatory support, and a collaborative effort across the industry.

Conclusion

The aviation industry is at a crossroads. Challenges like manufacturing delays, supply chain disruptions, and geopolitical tensions are testing traditional business models. Yet, these same challenges are fuelling innovation and creating new opportunities, particularly in the aircraft leasing sector. One emerging priority is the need for tools and applications that help stakeholders make smarter investment decisions in leasing and fleet management. Understanding the details of lease structures and identifying the best options for pre-acquisition investments will be critical for maximising returns and minimising risk. These intelligent approaches can redefine how airlines and lessors manage portfolios in a dynamic market. At AerPrice, we are combining aviation expertise with technology to enable better decision-making and drive smarter aviation investments for lessors and investors. Reach out if you'd like to know more.

References

Business Insider. (2025). ‘Airbus had a way better 2024 than Boeing, delivering 766 commercial aircraft’. Available at: https://www.businessinsider.com/airbus-boeing-better-year-aircraft-deliveries-order-backlog-2025-1 . [Accessed 20 May 2025]
Financial Times. (2025). ‘Aircraft shortages will drag on for years, predict leasing bosses’. Available at: https://www.ft.com/content/10b9a040-0ef8-4348-89fc-f5ede131ab6f . [Accessed 20 May 2025]
Forbes. (2025). 'Aircraft Production Hurdles Create Record Order Backlog, Older Fleet'. Available at: https://www.forbes.com/sites/oliverwyman/2025/02/27/aircraft-production-hurdles-create-record-order-backlog-older-fleet/ . [Accessed 23 May 2025]
Reuters. (2023). ‘RTX engine issue will ground 350 planes per year through 2026’. Available at: https://www.reuters.com/business/aerospace-defense/rtx-expects-3-bln-hit-q3-pratt-whitney-gtf-engine-issues-2023-09-11 . [Accessed 23 May 2025]
SMBC Aviation Capital. (2024). ‘SMBC Aviation Capital and Trinity College Dublin today announce the Trinity College Dublin SAF Research Facility at SMBC Aviation Capital’. Available at: https://www.smbc.aero/news/2024/smbc-aviation-capital-announces-partnership-trinity-college-dublin-sustainable-aviation . [Accessed 23 May 2025]
SMBC Aviation Capital. (2025). 'Push and pull factors on aircraft lease rates 2025'. Available at: https://www.smbc.aero/sites/smbc.aero/files/2025-03/SMBC_AC_PushPull_Whitepaper_AW.pdf . [Accessed 23 May 2025]
The Times. (2024). ‘Rolls-Royce v BA: the debacle that grounded hundreds of flights’. Available at: https://www.thetimes.com/business-money/companies/article/rolls-royce-v-ba-the-debacle-that-grounded-hundreds-of-flights-6fsnjnvdb . [Accessed 23 May 2025]

Machines of the Mind: How Artificial Intelligence is Shaping Our World (History of AI)

Sun, 20 Oct 2024 14:10:07 GMT

10 minute read - The impact of artificial intelligence (AI) is sparking intense debates, even amongst the most influential and well-renowned industry leaders and public figures, on its potential to reshape jobs, industries, and society. It’s evident that we are entering an era of unchartered territory, but are we facing a utopia of innovation or a dystopian nightmare? With each of the previous major advancements of innovation there has always been one constant: fear. Fear of what the new innovation means for jobs, society, and the future. AI is no exception.

The Evolution of Revolutions

1st Industrial Revolution

Steam power, the hallmark of the 1st industrial revolution, completely transformed transport and manufacturing. Before steam power, horses were used to transport goods - an expensive, slow, and high-maintenance option. Horses had limitations of needing to rest, only carrying a certain weight, and requiring constant care to remain in good condition. Over the course of half a century, horses were replaced with more efficient machines. This shift spurred increased productivity, high wagers, and improved living standards.

2nd Industrial Revolution

The 2nd Industrial Revolution was fueled with new sources of energy: electricity, gas, and oil. This was one of the most prolific periods of change in the modern world, propelling industrial and city growth and enabling mass production. Henry Ford’s assembly line epitomised this era and in 1908, Ford’s Model T brought affordable cars to the masses - a transformation as disruptive as today’s AI-driven automation. This period saw cheaper mass production of everything from tools to weapons to transport.

3rd Industrial Revolution

The 3rd Industrial Revolution introduced digital communication, which forever altered how we transmit information, do business, and also interact with each other. New electronics allowed IT systems to automate production and handle supply chains on a global scale. Computers were no longer just tools for scientists - they became integral to everyday life, and reshaped how industries operated and how individuals connected with one another. Communication and information were as valuable as the products they enabled.

4th Industrial Revolution

The 4th Industrial Revolution started to blur the lines between humans and technology, as our devices and sensors have become extensions of who we are. Advanced biotechnology, robotics and AI are now converging, creating endless possibilities for innovation and challenging our very definitions of life and consciousness. AI, now advancing at a pace beyond human capacity, and will continue to push the boundaries of creativity and problem-solving - just like steam engines, electricity, and computers did before. But for the evolution of AI, we need to step back in time to 1950.

The Early Days of AI

1950: Alan Turing - “Can Machines Think”

In 1950, Alan Turing, who is also known for cracking the Enigma code during WW2, famously asked the groundbreaking question: “Can machines think?”. At that time, computers were limited to performing specific tasks like calculations while humans were employed by the likes of NASA to perform more complex problems such as rocket trajectories. Turning imagined a future where machines could go far beyond following instructions and instead learn, grow, and adapt - something unheard of at the time. He believed that at some point, machines could show intelligence, or even surpass humans. Though technology at the time could not prove his theory, he devised a test he called “The Imitation Game”, now known as the “Turing Test”, whereby a human interrogator interacts with both a machine and a human, aiming to determine which responses came from the machine. If the machine successfully fools the interrogator into thinking it is human, Turing argued, we should consider that machine capable of thinking, an outcome that has caused controversy in terms of whether this actually implies intelligence.

1955: Paving the Way

As computers began to store more information and became faster, more affordable, and more accessible, Turin’s question “Can machines think?” paved the foundation of what AI is built upon today.

1958: John McCarthy and the Birth of AI

John McCarthy, known as the father of AI, coined the term “artificial intelligence” in 1955. In 1956, he then organised the first major AI conference to explore how machines could mimic human reasoning, problem-solving, and self-improvement. One of his most significant contributions came in 1958 when he developed LISP, the first programming language for AI. LISP remains foundational, powering modern AI from robotics to voice recognition to fraud detection.

1961: Unimate - The First Industrial Robot

In 1961, AI took another major leap with Unimate, the world’s first industrial robot. Unimate, a hydraulic manipulator, began work at General Motors, performing dangerous tasks like welding and handling die castings. Its introduction revolutionised manufacturing - robots could now work tirelessly, increasing productivity, improving product quality, and reducing labour costs. Unimate also made factories safer, taking over hazardous jobs from humans. This innovation sparked widespread adoption of automation, transforming industries far beyond car manufacturing.

1966: ELIZA - The First Chatterbot

In 1966, ELIZA, the first chatbot, simulated a psychotherapist’s conversation style, using natural language processing to engage users. Though simple by today’s standards, ELIZA raised important questions about whether machines could convincingly mimic human dialogue. Interacting through typing in questions, people often felt they were talking to a real person, marking a huge step forward in AI's conversational capabilities. Its legacy continues today, influencing modern AI assistants like Siri and Alexa.

AI Boom & Winter

During the next couple of decades, AI experienced a period of significant highs and lows.

1980-1987: The AI Boom

The AI Boom saw rapid growth and widespread optimisms. Expert Systems were developed that could analyse data and make rule-based decisions. Deep learning techniques also emerged, allowing AI to learn from its mistakes, which paved the way for the first autonomous drawing program and driverless car. Governments saw the potential in AI and began funding research, AI conferences flourished, science and engineering was a sought after skill.

1987-1993: The AI Winter

But the AI Winter was only around the corner. The high expectations from the boom were not met due to their costly development and limitations that became apparent. Governments and private investors began cutting funding, AI research slowed, and public interest faded.

Back on Track

But despite these setbacks, innovation continued in the background. By the 1990s, AI research began to bounce back. Machine learning algorithms became more efficient, laying the groundwork for integration into the healthcare and finance industries, demonstrating the ability for these technologies to transform industries and everyday life.

Key Milestones

1997: Deep Blue Beats Garry Kasparov

One of the most historic moments for AI took place on a chessboard in 1997. Chess, long considered the ultimate test of human intellect, creativity, and strategy, now became the stage for a larger battle - whether AI could surpass human cognitive abilities. IBM’s Deep Blue, a supercomputer designed for chess, defeated world champion Garry Kasparov, marking the first time a computer triumphed over a reigning champion under standard tournament conditions. But this wasn’t just a chess game, the match represented a symbolic clash between human ingenuity and machine precision, captivating audiences worldwide. Deep Blue showcased the power of brute-force computing, evaluating 200 million chess positions per second, yet its victory raised questions about the nature of intelligence, as it relied on computational power rather than creativity. Nevertheless, this event paved the way for AI to enter public consciousness and symbolised the growing potential for AI to challenge human expertise across various fields.

1997: Speech Recognition

While Deep Blue was making headlines, 1997 also saw a significant breakthrough in speech recognition with Dragon Systems releasing its software for Windows. This technology enabled computers to convert spoken words into text, laying the groundwork for natural language processing. Though initially limited - requiring user training and struggling with accents, it marked the start of making machines more intuitive. Over the following years, speech recognition evolved into mainstream virtual assistants, leading to innovations like Apple's Siri, Amazon Alexa, Microsoft Cortana, and Google Assistant, fundamentally changing how we interact with technology. Today, we use virtual assistants to schedule meetings, set reminders, control smart devices, and even answer philosophical questions. This technology, now an essential part of modern life, owes its roots to the pioneering work of the late 90s.

2000: Robotic Emotion

As AI advanced into the 21st century, the focus shifted toward creating machines that could not only process data but also simulate emotions and interact with humans on a more personal level. In 2000, Professor Cynthia Breazeal from MIT developed Kismet, the first robot capable of mimicking human emotions through facial expressions. Kismet’s design enabled it to engage in emotional communication, laying the foundation for affective computing. Kismet's innovation laid the groundwork for more advanced social and emotional AI systems.

This concept evolved with the introduction of Sophia by Hanson Robotics in 2016, a humanoid robot capable of recognising and responding to human emotions. Sophia can hold conversations, express opinions, and make facial expressions that mirror human reactions. Her lifelike appearance and advanced AI allow her to interact in ways that feel almost human. Sophia became a celebrity, engaging with industries, appearing in interviews, and even addressing the United Nations, along with being granted Saudi Arabian citizenship, pushing the boundaries of human-robot interaction. Sophia represents a significant leap in human-robot interaction, raising profound questions about consciousness and emotion. As AI continues to advance, it’s clear that robots are no longer just tools - they are entities that can interact with us on a personal, emotional level, reshaping the role of machines in our lives.

2003: Robotic Navigation

The early 2000s marked impressive advancements in autonomous robotics, highlighted by NASA's successful landing of the Spirit and Opportunity rovers on Mars. Equipped with AI systems, these rovers could navigate the surface independently, analyse terrain, avoid obstacles, and make decisions without human intervention. Their success demonstrated the potential of autonomous systems in challenging environments and inspired the development of ground-based robots. These progressed with companies like Boston Dynamics creating agile robots capable of navigating complex terrains without human guidance, enhancing safety and efficiency across various industries, and ushering in an era where machines actively collaborate with humans. With each advancement, we're entering new eras where machines don’t just follow commands but work alongside us, enhancing our capabilities and pushing the boundaries of innovation.

2006: Personalised AI

In the late 2000s and early 2010s, AI began to significantly influence social media, gaming, and streaming services. By harnessing vast amounts of user data, companies started utilising AI to deliver tailored content and enhance user user experience (UX). For instance, Facebook improved its news feed algorithm to display posts most relevant to users based on their activity, while Netflix used AI to recommend shows and movies according to viewing history. This data-driven approach transformed entertainment by making platforms more engaging and completely changed the way people consume entertainment.

A key milestone came in 2010 with the launch of Microsoft’s Xbox 360 Kinect, the first gaming device to track body movement without a controller. This innovation employed AI, computer vision, and machine learning to create an immersive gaming experience. Overall, this era marked AI's transition from industrial applications to everyday consumer technology. The increasing data collection allowed these systems to learn and evolve, paving the way for more advanced AI applications to personalise, predict, and enhance experiences in the future.

2016: AlphaGo Beats Lee Sedol

In 2016, we witnessed a groundbreaking moment in AI with the creation of AlphaGo, developed by Google DeepMind. This wasn’t just another step in AI’s evolution; it was a monumental leap into a realm many believed would remain out of reach for machines for years to come. Go, an ancient board game from China, has long been considered the ultimate test for AI. Unlike chess, which has a finite number of possible moves, Go is vastly more complex, offering nearly infinite moves at any given moment.

Historically, AI struggled to master Go, despite being seen as a perfect testing ground due to its clear rules. Previous AI systems had only achieved intermediate levels of play. However, AlphaGo distinguished itself by utilising neural networks and machine learning, learning from a dataset of thousands of human games rather than relying solely on brute-force calculations. AlphaGo’s victory captivated global audiences as it highlighted AI's potential to enhance human creativity. During its victory, it displayed creative moves that Go players have since used to learn from, prompting a reevaluation of human-machine interaction, illustrating that AI could not only compete with human intelligence but also provide new insights into complex problems.

Following its success, AlphaGo evolved into AlphaGo Zero, which trained itself without human data, and then AlphaZero, which could play multiple games like chess and Shogi, showcasing AI's flexibility. These developments underscored AI's ability to exceed human understanding in certain domains, raising important discussions about the opportunities and challenges posed by such technologies. Overall, AlphaGo's triumph was a significant milestone, demonstrating AI's capacity to innovate and inspire.

Conclusion

As we reflect on the pivotal moments in AI’s development, it’s clear how instrumental these milestones were in reshaping how we interact with technology in our daily lives. The integration of AI into social media, gaming, and streaming services marked a transformative shift, enabling platforms like Facebook and Netflix to offer hyper-personalised experiences that engage users in unprecedented ways.

The groundbreaking achievement of AlphaGo in 2016 further highlighted AI's potential, showcasing its ability to learn, innovate, and even teach us new strategies in the ancient game of Go. AlphaGo not only captivated the world but also opened up discussions on AI's future implications for creativity, problem-solving, and our relationship with technology.

As we stand on the cusp of new developments in AI, it’s essential to consider both the incredible opportunities and the challenges these advancements present. From personalised experiences in our everyday apps to sophisticated AI agents that augment human intelligence, the journey of AI is far from over.

Stay tuned for Part 2, where I’ll continue exploring our current landscape with ChatGPT and other AI agents, as well as what the future has in store for us.

Until next time. I hope you enjoyed the read. GB.

Hashtags

#AI #ArtificialIntelligence #DataScience #MachineLearning #ML #DeepLearning #NeuralNetworks #Technology #Tech #HistoryOfAI #EvolutionOfAI #Data #DecisionMaking #IndustrialRevolution

References

Alan Turing (1950) - Can Machines Think. Available at: https://awl.com/news/alan-turning-computer-lgbtiq-trailblazer/ . [Accessed 10 October 2024]
AlphaGo Beats Lee Sedol (2016). Available at: https://www.theatlantic.com/technology/archive/2016/03/the-invisible-opponent/475611/ . [Accessed 10 October 2024]
Boston Dynamics - Do You Love Me?. Available at: https://www.youtube.com/watch?v=fn3KWM1kuAw . [Accessed 10 October 2024]
Deep Blue Beats Garry Kasparov (1997). Available at: https://www.washingtonpost.com/history/2023/05/22/garry-kasparov-chess-deep-blue-ibm/ . [Accessed 10 October 2024]
ELIZA Chatbot (1966). Available at: https://www.maths.cam.ac.uk/internal/faculty/files/swh/swh.jpg . [Accessed 10 October 2024]
John McCarthy (1955). Available at: https://www.maths.cam.ac.uk/internal/faculty/files/swh/swh.jpg . [Accessed 10 October 2024]
Sophia the Robot by Hanson Robots: Available at: https://www.youtube.com/watch?v=BhU9hOo5Cuc . [Accessed 10 October 2024]
Unimate Robot (1961). Available at: https://robotsguide.com/robots/unimate/ . [Accessed 10 October 2024]

The Future Reframed: From Prompt to Product

Tue, 07 Mar 2023 20:58:18 GMT

10 Minute Read - Last week, I got the opportunity to take part on the “Future Focus – What’s Next for Technology?” panel at the Mason Hayes & Curran LLP Technology Conference – Talent, Funding, and the Future. This conference showcased expert panels and thought-provoking discussions dealing with topics around recruitment, talent, equity, investment, and technology. The following is an overview of my panel discussing the value and limitations of ChatGPT, how business should approach adopting AI, the ethical considerations surrounding this technology, and what's coming next. All thoughts and comments are my own.

Chatting You Up

ChatGPT has been taking the technology world by storm since it's launch late last year. I haven't seen this much excitement since Boston Dynamics came out with their robots dancing to "Do You Love Me" from the movie Dirty Dancing (Boston Dynamics, 2020). Over 1 million people had signed up within the first five days and 100 million users in just over one month (CNBC, 2023). But this is the first time that I've actually seen mass excitement/concern from the technology community, programmers specifically, within such a short space of time around a piece of technology. This is due to the combination of how creative the output from this can appear and also the fact that it can write code.

From Words to Code

From a technical point of view, you can ask it to write you a piece of code that will generate a type of functionality that is written in a particular coding language. Although it does require some hand-holding on this particular area, this is a significant advancement in development allowing additional support for basic coding, validation, testing, security scanning, debugging, and other time intensive tasks, allowing developers to focus more on the creative and difficult coding tasks.

How Creative Is It?

From a creative point of view, you can ask for a song to be written that focuses on a specific topic in the style of your favourite artist, and within seconds you have something that is good enough to sing in the shower. You can also ask it to write you an essay in a specific style focusing on a particular point and include references, and again within seconds you have something that can get a decent grade from a professor. As a result, a number of universities across the world have banned the use of ChatGPT (Business Insider, 2023), others are looking for ways to include it within it's curriculum (Voice Bot, 2023), and some Irish universities are discussing new ways to assess and adapt assignments (Irish Times, 2023).

How Believable Is It?

A good example of this comes from psychologist and author Jordan Peterson. The author of the Books "12 Rules for Life" and "Beyond Order" asked ChatGPT to write him an essay "that’s a 13th rule for "Beyond Order", written in a style that combines the King James Bible with the Tao Te Ching". He then went on to say how impressed he was that it wrote him 4 pages and it wasn't obvious and he wouldn't have been able to tell that he didn't write it (Modern Wisdom, 2022) .

What Are the Limitations?

All of the above sounds incredible. And in fairness, it really is. But it's important to note that there are some limitations and considerations when it comes to it's use. An example of some are the following:

It does not have a direct connection to the internet . Therefore any real-time information like sports score, stock prices, etc... cannot be accessed.
2021 was the last data that it was trained on . Therefore anything that has happened since 2021 cannot be incorporated into its responses.
The responses are largely based on patterns and therefore may also be inaccurate . As a result, Stack Overflow, the populate developer community, banned users from responding with AI generated answers due to inaccurate results (The Verge, 2022).
As it's based on training data, the bias and stereotypes that exist from its sources may be apparent in the responses.
The responses will not have common sense or emotional intelligence and therefore may be lacking in empathy and an understanding of complex emotional or social situations.
It is currently a text-based model, and therefore cannot respond to visual or audio input .

Good Prompt, Great Response

With the above being said, it highlights the importance of a good prompt. The majority of negative attention around ChatGPT is based on poor instructions or prompts that result in basic or generic responses. There seems to be an art and number of important aspects to creating a better prompt; from defining the role of which you want the response to be returned (e.g. act as a professor) to providing all the context (i.e. provide as much detail as possible). So it's clear that the more information you provide, the better you structure your questions, and the more details you provide in terms of how you want your response, the better the result will be. Either way, the response is a fantastic starting point and a solid foundation to build from.

The Business Value

From a business point of view, this type of technology can be leveraged in a number of ways. For example, ChatGPT can be used in the following ways:

Customer support : A chatbot that is available 24/7 to handle support queries which can result in increased customer satisfaction due to quicker response times.
Personalisation : A detailed understanding of the customers' preferences and needs resulting in more aligned recommendations that lead to a higher likelihood of the customer conversions.
Content creation : Generate consistent product descriptions, brochures, and other marketing material quickly and efficiently.
Marketing : To assist and create email campaigns and social media posts, and optimise based on customer data with the intended result of better engagement.
Research : Analyze large amounts of data to delve into customer behaviour, market trends, competitor analysis, etc., enabling the business to make more informed decisions around strategies and growth.

Build or Buy When It Comes To AI

The build or buy discussion expands across many industries, but when it comes to realising true value from technology, there are a number of important factors that must be considered; defining the business value, developing the appropriate use-cases, budgeting the required investment, identifying the team required and also aligning to skills to expertise, all of which I discussed in more detail in a recent article “ Industry Future of AI for Health and Wellness ”. There are pros and cons of either direction, but it's important to really focus on understanding the answers to the following:

Intention : If you want to retain the knowledge internally, build something that's core to your proposition, and potentially have IP associated, the build is your best option. If it's just going to be used as a small part to a larger product, then buy is probably your best bet. But it's important to consider not only the factors outlined above, but expanding on the following:
Budget : Buying technology can be a large upfront investment, but building in-house will require a significant investment in time, money, and also resources. It's important to consider your budget and understand what option is more feasible in the long term.
Skills & Expertise : To build internally, you will need to compile a team of experts across data scientists and software engineering. If you already have this team and skills available, it may not be a major uplift to build in-house. However, if you need to build up the team and skill set required to deliver internally, buying could be a better option.
Flexibility : If you require a very customised and unique approach to understanding and handling your data, you may need to build in-house to ensure flexibility in adapting to your specific needs. But if it's quite a standard approach you are looking for and doesn't require too much customisability, buying something in may be more aligned to your needs.
Time to market : In order to build an application from scratch takes a lot of time and effort. If your needs are to get to market as quickly as possible, buying something in would be a lot quicker (in the majority of cases) than building internally.

Data-Driven Challenges

Another important and overarching aspect to consider is the the challenges associated with becoming data-driven (i.e challenges associated with collecting and structuring the data):

Objective Identification : It can be difficult to combine the right people and knowledge in order to understand the value of the data in alignment with the strategic direction of the business.
Secure Accessibility & Integration : During business growth, data systems can sometimes become disjointed due to the expansion in the various applications, services, and databases, making it hard to integrate and centralise the data.
Cultural Resistance : Humans are a creature of habit, so introducing new procedures and processes can often result in some sort of adoption hesitancy.
Data Overload & Trust : Consolidating and validating data being retrieved from a range of difference sources can be difficult, and often results in the valuable data not being utilised.

Ethical Considerations

In my 3-part series of ethics within AI, I talked about the privacy when it comes to handling personal data, content ownership when it comes to who owns the content created by non-humans, and also ethical strategy when it comes to setting up regulations around the technology - some of which I also discussed during this panel.

" As we move more into the creation of content by AI, the topic of copyright ownership will become increasingly more intriguing " - Graham Baitson

Plagiarism

But one area I wanted to delve into in a little more detail here, specifically related to ChatGPT, is around plagiarism. As mentioned above, universities all over the world are trying to figure out how best to handle the use of ChatGPT when it comes to students submitting content. As a result, Turnitin, the internet-based plagiarism detection service, has officially developed software to detect if a student has used an AI chatbot (The Tab, 2023).

Referencing a point I make above in relation to copyright ownership when content is created by a non-human, the definition of plagiarism can be stated as the act of taking someone else's work and passing it off as your own with giving credit. But this definition becomes clouded due to the nature of when the work has been created by something rather than someone.

Either way, it's opening up a lot of interesting discussions, and making universities rethink the definition of plagiarism and whether AI is ultimately being used as a research tool or a cheating device (Wired, 2023).

The Future

At present, the majority of these technologies and tools all act independently. During the last couple of days, OpenAI introduced their ChatGPT and Whisper APIs to developers allowing them to integrate ChatGPT and Whisper models into their applications and products through their API (OpenAI, 2023).

" The real value will only become apparent when all the disparate AI technologies are all joined up and working together " - Graham Baitson

From Prompt to Product

To me, this is the beginning of realising the true potential of these AI tools. We are not too far away from being able to prompt a tool into creating a new product that doesn't exist. The tool will then go off and develop the website, generate the marketing and the social media content, create the complementary images and video material, outline the CAD drawing necessary to build the product, and then send it off to a 3D printer to be printed. From prompt to product. To me, this is the future.

Final Comments

I chose to study technology because I knew it would become such an influential part of our everyday lives, so it was such a privilege to meet so many fascinating people and contribute alongside Oisín Tobin and Brian McElligott from Mason Hayes & Curran LLP , Garret Molloy from Citi , and Sohini De from Empeal Health to discussions around artificial intelligence (AI) and how technology will impact the future of business.

There’s always a question around whether AI will replace jobs. I've discussed this extensively in my article " Are Humans the Next Horse? The Rise of the Robots ", but one thing is now for sure, the people and companies who don't utilise AI, will be replaced by the people and companies who do. This is the worst AI will ever be. It's only going to get better from here.

Until next time. I hope you enjoyed the read. GB

Hashtags

#AI #ArtificialIntelligence #DataScience #MachineLearning #ML #Technology #Tech #Trustworthy #Ethics #Policy #Regulations #Governance #Data #DecisionMaking #Compliance #Privacy #Ownership #Copyright #Content #MHCLaw #MHCTech #TechLaw #TechnologyLaw #Talent #Future #Funding #FutureOfWork

References

Boston Dynamics. (2020). ' Do You Love Me? '. Available at: https://www.youtube.com/watch?v=fn3KWM1kuAw . [Accessed 4 Mar 2023]
Business Insider. (2023). ' Here are the schools and colleges that have banned the use of ChatGPT over plagiarism and misinformation fears '. Available at: https://www.businessinsider.com/chatgpt-schools-colleges-ban-plagiarism-misinformation-education-2023-1 . [Accessed 4 Mar 2023]
CNBC. (2022). ' All you need to know about ChatGPT, the A.I. chatbot that’s got the world talking and tech giants clashing '. Available at: https://www.cnbc.com/2023/02/08/what-is-chatgpt-viral-ai-chatbot-at-heart-of-microsoft-google-fight.html . [Accessed 4 Mar 2023]
Irish Times. (2023). ' Irish universities to review how they assess students following threat posed by AI chatbot '. Available at: https://www.irishtimes.com/ireland/education/2023/01/18/irish-universities-to-review-how-they-assess-students-following-threat-posed-by-ai-chatbot/ . [Accessed 4 Mar 2023]
Modern Wisdom. (2022). ' Jordan Peterson's Disturbing Warning About AI and ChatGPT '. Available at: https://www.youtube.com/watch?v=mUkTz_1uzSs . [Accessed 4 Mar 2023]
OpenAI. (2023). ' Introducing ChatGPT and Whisper APIs '. Available at: https://openai.com/blog/introducing-chatgpt-and-whisper-apis . [Accessed 4 Mar 2023]
The Tab. (2023). ' Uh oh! Turnitin is officially going to detect if you’ve used an AI chatbot in your essay '. Available at: https://thetab.com/uk/2023/02/09/turnitin-chatgpt-essay-detection-294120 . [Accessed 4 Mar 2023]
The Verge. (2022). ' AI-generated answers temporarily banned on coding Q&A site Stack Overflow '. Available at: https://www.theverge.com/2022/12/5/23493932/chatgpt-ai-generated-answers-temporarily-banned-stack-overflow-llms-dangers . [Accessed 4 Mar 2023]
Voice Bot. (2023). ' ChatGPT is Banned by These Colleges and Universities '. Available at: https://voicebot.ai/2023/02/09/chatgpt-is-banned-by-these-colleges-and-universities/ . [ Accessed 4 Mar 2023]
Wired. (2023). ' ChatGPT Is Making Universities Rethink Plagiarism '. Available at: https://www.wired.com/story/chatgpt-college-university-plagiarism/ . [Accessed 4 Mar 2023]

Human and AI Collaborative Intelligence

Mon, 28 Nov 2022 14:07:44 GMT

5 Minute Read - There's a lot of deliberation around whether the rise and development of full artificial intelligence will threaten human existence (more of which can be read in my article ‘ Are Humans the Next Horse? The Rise of the Robots ’). Whether or not this is true, only time will tell, but we can definitely say for certain that most advancements in technology will pose security risks as a result of poorly designed, misused, or hacked systems with little or no integrated regulations.

Human on the Loop

A key area that is touched upon during a lot of AI conferences and articles is the importance of ensuring a human element within the process of developing AI solutions. A healthy combination of automation and human collaboration allows for the build of trust within these systems, especially ones that are prone to change, have inherent uncertainty, require governance oversight, or have critical consequences as a result of decisions being made. One interesting consideration by Jean-François Gagné, Head of AI Product Management and Strategy at ServiceNow, is around the differences when designing either ‘human in the loop’ or ‘human on the loop’ systems.

Depending on the type of application and the expected outcomes, it is important to choose the correct type of system. In a recent defence article, Terrence J. O’Shaughnessy, commander of the United States Northern Command and of the North American Aerospace Defense Command (NORAD), stated that the military should move from a human in the loop model (where a human still has control over stopping and starting actions) to a human on the loop model (still allowing oversight, but not requiring pre-approval, and pushing human control farther from the centre of the automated decision-making (FedScoop, 2020).

Diverse and Cognitive AI

Almost all conversations around AI will eventually make its way towards discussing ethics. I have written a number of articles touching and focusing on ethical AI including ' Are Humans the Next Horse? The Rise of the Robots ' and also my 3-part series starting with ' The Rise of Ethics in Artificial Intelligence (Part 1: Privacy) '. There are a number of important factors that need to be considered when building within a collaborative environment:

Leadership : When good leadership is in place, almost anything is achievable. Leadership sets the example, which should then be followed by having a combination of complimentary product, technology, and compliance teams at the table for decision making.
Partnerships : When at the cutting-edge of technology, it is crucial to know how to look for opportunities to build relationships and form partnerships by having dynamic links with technology, industry, and regulatory frameworks.
Ethics-Aware : It’s not enough just to teach ethics, you need to teach people how to be ethical. This process should be embedded not only into the technology teams, but across the entire company. This ground-up awareness ensures that there is alignment across all aspects of the product life-cycle towards developing secure, transparent, and connected products.
Users : When building products, you need to consider the societal and generational balance to understand how users will interact and use the applications. User experience design (UX) should be at the heart of the products and act as an extension to the customers, enabling them to part of the creation journey and see the benefits from the starting position of understanding risk and usage.

Final Thoughts

In a recent article, a Google engineer stated the company's AI has become sentient (CBC News, 2022). The sentient debate touches on technology, ethics, and philosophy in the understanding of what it means to be alive and whether we will ever fully know if AI has gained consciousness. Either way, there is a huge amount of progress that needs to be made before AI can be fully autonomous - if it ever will be, and will require a huge amount of human effort to shadow it along the way. Do you ever think AI will become fully sentient? Until next time, I hope you enjoyed the read. GB.

Hashtags

#AI #ArtificialIntelligence #DataScience #MachineLearning #ML #Trustworthy #Ethics #Policy #Regulations #Governance #Data #DecisionMaking #DocumentIntelligence #DueDiligence #Complianc e

References

CBC News. (2022). ' A Google engineer says AI has become sentient. What does that actually mean? '. Available at: https://www.cbc.ca/news/science/ai-consciousness-how-to-recognize-1.6498068 . [Accessed 10 July 2022]
FedScoop. (2020). ‘ AI needs humans ‘on the loop’ not ‘in the loop’ for nuke detection, general says ’. Available at: https://www.fedscoop.com/ai-should-have-human-on-the-loop-not-in-the-loop-when-it-comes-to-nuke-detection-general-says/ . [Accessed on 13 December 2021]
Figure Cover. (2020). The Conversation. [online] Available at: https://theconversation.com/will-ai-take-over-quantum-theory-suggests-otherwise-126567 . [Accessed 13 December 2021]
Gagné, Jean-François. (2021). ' Designing for the Humans in the Loop – Part III '. Available at: https://jfgagne.ai/blog/designing-for-the-humans-in-the-loop-part-iii . [Accessed 15 December 2021]

Evolving AI’s Availability to Transform our Future

Tue, 05 Jul 2022 18:42:28 GMT

6 Minute Read - At our recent AI Possible Summit, I got the opportunity to moderate a panel on emerging technology. I was joined by some amazing people to discuss how to increase AI's availability and how it's being applied to different industries. The following is an overview of this panel. All thoughts and comments are my own.

Introduction

One of the reasons why I love working in technology is that I get a chance to meet and discuss lots of interesting topics with some fascinating people. Recently during Altada's inaugural AI Possible Summit in Miami, the purpose of which was to unearth new opportunities around AI and explore how having a diversity of talent results in a positive impact for businesses, I got an opportunity to moderate the keynote AI and Emerging Technologies panel discussing topics around software development, data science, data ethics, privacy and security, performance modelling, along with the future impact of how AI is being applied within media, entertainment, NFTs, the Metaverse, and more.

Development Lifecycle / AI Deployment

When considering the development of AI, people often think of a data science team creating algorithms. While this is true, there are a number of additional and supporting services required to transform that AI algorithm into a commercial product. Sarah O’Connell, Head of Software Engineering at Altada, gave an overview of how teams such as software development, cloud platform, emerging technology, UI/UX, and technical delivery, need to collaborate together to augment the data science elements when creating end-to-end world class solutions capable of scaling and providing value.

When considering the integration between each of these functional areas, it’s important to consider the role that data plays and how to ensure that data is kept secure and handled ethically, a topic that I have previously discussed in my article “ The Rise of Ethics in Artificial Intelligence (Part 3: Trustworthy AI) ”. Mark Woolnough, Senior Portfolio Solution Architect at Nordcloud, gave a really detailed outline on the importance of having a data strategy that focuses on data ethics, security, software architecture, and containerisation for accelerating deployment of AI.

One of the challenges surrounding the deployment of AI applications is that many people think the AI lifecycle stops at the deployment stage. Hakim Elakhrass, CEO & Co-Founder of NannyML, discussed how NannyML are combatting the issues that arise during the quick performance deterioration on AI models and the impact that this has on business metrics. One interesting concept here is the definition around AI performance. Is it based on technical metrics, on business impact, or even possibly both, and how the relationship between these change over time due to the dynamic systems. An example of this can be seen when Zillow, leading real estate marketplace, systematically overpriced 7000 houses by $300 million due to lack of machine learning performance monitoring (The Guardian, 2021).

Kevin Sharpley, COO & Co-Founder of Xavatar, discussed how being data-driven and having an understanding of how to use that data, a topic that I have also discussed in my recent article “ Using AI to Unlock the Value of your Data - Managing Non-Performing Loans (NPLs) ”, allows companies to capture the market share, retain their current users, and also attract new users to your product.

Support & Collaboration

You would have heard the proverb “ It takes a village ”. When used within a business context, it means that there is a better chance of success and enhanced value when working within a collaborative environment, which is evident from recent studies that show the average return on collaboration is four times the initial investment (Forbes, 2012). Kevin shared his experience of working with Altada during our Alsessor AI Accelerator, the final of which took place this week, emphasising that it has allowed them to look at AI in a holistic way.

Having strong support and collaboration networks enhance the creation of meaningful and valuable products. Mark discussed how having the right combination of people with technical expertise and industry/domain expertise will result in breaking down barriers, having a better understanding of data, and becoming more productive when creating technical solutions.

Since 1975, the most important asset for organisations have gradually flipped from 83% being physical assets, to now 84% being human capital (PCMA, 2021). Hakim said that not only is the most important thing to do when growing an organisation is finding the right people, but also enabling them with a good culture to allow them to thrive and do their best work.

“A very important question that you should ask yourself is what type of organization do you want to build” – Hakim Elakhrass, CEO & Co-Founder of NannyML

But finding these right people can prove to be a difficult process, with 82% of companies believing they are unable to attract the correct talent (McKinsey, 2017). In my recent article “ Rethinking Talent to Thrive In An Agile AI World ”, I highlighted some ways in which AI is impacting the talent market. Adding to this, Sarah also discussed how best to leverage the ecosystem to support the talent pipeline by forming partnerships to bring innovation into the product workflow and also addressing the skills gap through university engagements.

Future and Beyond

With the pace of new advancements within emerging technologies, it’s unrealistic to expect everyone to be an expert across multiple domains. So how do we ensure that companies stay ahead of the curve and keep abreast of the market direction? Sarah brought up the topic of creating micro-teams to focus on specific emerging areas with the intention to create reusable components, through micro-services and API first approach, that can be utilised across the business without everyone requiring the deep knowledge or expertise.

Companies who understand how to apply these approach and base decisions on metrics and data, will reap the beneficial rewards. But will companies start to automate actions and direction based on these data points? Hakim introduced the term of ‘hedge-fundification’ outlining that as more companies start to utilise machine learning to make critical conditions, they will start to operate more like a hedge fund. But the challenge around this is that hedge funds operate understanding and preparing a strong risk culture and risk management, so therefore it’s imperative for traditional enterprises to understand this risk and possible dramatic effects due to making these more analytical decisions on the output of models.

But how available is AI to enable companies to obtain the maximum benefit? We have seen the evolution of technology from the first computer being “ 50 foot long, weighing give tons, and consisting of 750,000 separate parts ” (Britannica, 2001), to know being able to fit supercomputers in our pocket. Mark outlined how that evolution is continuing with manufacturers now releasing their products with on-chip AI models that can at completely replace, but at minimum augment and support, human decisions and processes, enabling real-time and proactive monitoring..

Final Thoughts

As these technology and manufacturing advancements become more mainstream, the ability to take advantage of their capabilities will result in a creating a wave of new innovations and opportunities. The evolution from narrow AI (more focused) to broad AI (wider reach and increased capabilities) to general AI (off the shelf solutions that can be applied to solve many challenges) has enabled the brightest minds to come together and create products and services that are changing the world and how we live. As we move into the unknown in terms of potential, the transparency and explainability of how these systems interact and make decisions will need to be at the forefront of development. The advancements in areas such as quantum, will create the computing ability for these products to run analysis, predictions, and make decisions in real-time. Relationships between human and machine interaction will be absorbed and immersed into interactive, virtual, and augmented environments like the Metaverse and Xataverse enabling a whole new range of experiences and connections. Would you like to visit space? Plug yourself in the Xataverse and off you go.

You can visit https://www.altada.com/aipossible/keynotes/ if you want to watch this panel discussion. Until next time. Hope you enjoyed the read. GB

Hashtags

#AI #ArtificialIntelligence #ML #MachineLearning #DataScience #SoftwareDevelopment #Data #Ethics #Talent #Security #Performance #AR #AugmentedReality #Metaverse #Xataverse

References

Britannica. (2001). “ The first computer ”. Available at: https://www.britannica.com/technology/computer/The-first-computer . (Accessed 24 June 2022).
Forbes. (2012). “ 10 Tips on the Value of Collaboration in Startups ”. Available at: https://www.forbes.com/sites/martinzwilling/2012/05/10/10-tips-on-the-value-of-collaboration-in-startups/?sh=7d98cf653e69 . (Accessed 23 June 2022)
McKinsey. (2017). “ Attracting and retaining the right talent ”. Available at: https://www.mckinsey.com/business-functions/people-and-organizational-performance/our-insights/attracting-and-retaining-the-right-talent . (Accessed 24 June 2022)
PCMA. (2021). “ Since Pandemic, ‘Employees Have Become a Company’s Most Valuable Asset’ ”. Available at: https://www.pcma.org/pandemic-employees-have-become-companys-most-valuable-asset/ . (Accessed 24 Jun 2022)
The Guardian. (2021). “ The $300m flip flop: how real-estate site Zillow’s side hustle went badly wrong. The Guardian ”. Available at: https://www.theguardian.com/business/2021/nov/04/zillow-homes-buying-selling-flip-flop (Accessed 23 June 2022)

Using AI to Unlock the Value of your Data - Managing Non-Performing Loans (NPLs)

Tue, 26 Apr 2022 12:48:39 GMT

6 Minute Read - Last month I got the opportunity to give a Special Address presentation at Finovate Europe; a conference showcasing cutting-edge banking and financial technology through a unique blend of short-form demos and key insight presentations from thought-leaders. The following is overview of my talk. All thoughts and views are my own.

Challenges Becoming Data-Driven

Studies have shown that the majority of companies who understand their data, obtain true benefits and value as a result of being able to make more informed decisions along with the ability to adapt and respond to changes quickly. In one of my previous articles “ The Analytics Summit 2021 Trends - Data, Sustainability & Ethics ”, I mentioned that only 37% of the 85% of businesses that aim to be data-driven are successful. The reason why so many of these businesses fail, is due to a number of challenges when it comes to data collection and usage:

Objective Identification : It can be difficult to combine the right people and knowledge in order to understand the value of the data in alignment with the strategic direction of the business.
Secure Accessibility & Integration : During business growth, data systems can sometimes become disjointed due to the expansion in the various applications, services, and databases, making it hard to integrate and centralise the data.
Cultural Resistance : Humans are a creature of habit, so introducing new procedures and processes can often result in some sort of adoption hesitancy.
Data Overload & Trust : Consolidating and validating data being retrieved from a range of difference sources can be difficult, and often results in the valuable data not being utilised.

However, the companies who are successful in overcoming these challenges, show a number of common traits such as:

Persistence : They have firm continuation in their course despite any difficulties or obstacles.
Resilience : They have an ability to adapt and recover from setbacks or failures.
Great Execution : They put a plan in place, provide the necessary resources, and then drive towards execution.

Leveraging Artificial Intelligence (AI)

Considering these challenges outlined above, many companies look to leverage a technical solution to get a solid grasp of the value within their data. AI is a prime candidate to supercharge human thinking when it comes to understanding and unlocking data value by enabling patterns to be recognised, contexts to be visualised, and more informed decisions to be made. A recent study showed that 75% of executives fear going out of business within five years if they don’t utilise AI to understand their data (Semrush, 2021). But there are also a number of industry challenges associated with businesses trying to adopt AI. These come down to understanding the business value, identifying appropriate use-cases, applying reasonable investment to realise potential, employing the correct people with the right skills and expertise, and also the challenges associated with collecting and structuring the data, all of which I discussed in more detail in a recent article “ Industry Future of AI for Health and Wellness ”.

Financial Services

One industry that relies heavily on data to drive informed decision-making is financial services. For example, if you look at asset management, contract intelligence, and due diligence, they all have their own individual problems and tackle them in their own individual way, but one challenge that’s common across them all is that they need to ingest large amounts of documents and large volumes of data in a short space of time. Some of these documents may have been digitised 10-15 years ago when many laws and structures were different, in some cases these documents may not have been scanned to the highest quality, and a high majority of these documents contain unstructured data where it can be really difficult to use automated approaches to define and extract the key and relevant pieces of information. A recent study estimated that 85% of all data residing in an organisation is unstructured (expected to grow 2x in next couple of years) and only 2% of this data is being utilised in a meaningful way (Datamation, 2017). So understanding the data within these documents is a real challenge.

Non-Performing Loans (NPL)

One focus within the financial services industry that can really benefit from understanding their data is NPLs. An NPL, which traditionally follows the trajectory pattern outlined below, is where the borrower has failed to make any of the scheduled payments, normally within 90 days. Looking at the current crisis that started at the beginning of 2020 due to the Coronavirus, should the NPLs follow the same pattern (i.e. the mean time from the start of the crisis to the peak of the NPL ration being 3.3 years), the NPL peak could be reached in the first half of 2023.

When this happens, banks normally group these NPL portfolios into batches and put these out for tender – with the aim to sell them to the likes of secondary banks and asset managers in order to free up capital and/or focus on performing loans that bring in income. (Investopedia, 2021). During this bidding process, the data contained within all these NPLs (potentially millions of pages) will need to be analysed and value identified in order for the bidders to make an appropriate bidNew Paragraph.

Current Approach (Manual Processing)

At the moment, this portfolio exploration is a very manual process that is time consuming, expensive and prone to errors. A typical loan portfolio may contain hundreds of unstructured documents which are inconsistent and can vary widely based on originator, vintage, or even scanned image quality. Resources are required to manually read through these millions of data points, and although we sometimes like to think that we are perfect, humans make mistakes. After a certain amount of time reading through these documents with varying levels of quality, tiredness will start to kick in and the monotonous nature of performing the same task over and over will start to introduce errors and inaccuracies such as 3’s becoming 8’s, 5’s becoming 6’s, and a decimal point being shifted. So when the NPL peak hits (estimated to be Q1/Q2 of 2023), companies can either choose to spend a lot of time, money, and resources, or they could just use the solution that we have developed.

Utilising an AI Document Intelligence Platform

In order to ensure that decisions are not being made using this inconsistent data, AI document intelligence platforms are being developed that are trained to catalogue, extract, and understand key data within loan portfolios. These solutions utilis a combination of technologies such as object character recognition (OCR) to extract the key components of the document, natural language processing (NLP) to understand the context on that content, and a range of machine learning (ML) and AI techniques to categorise and analyse the data.

In a recent statement, Jason Pinson who is CEO of Rocktop Partners, a large investment manager outlined that "AI solutions have given our business the competitive edge in the market with transformational operational and cost efficiencies, such as the reduced cost of processing a loan file from $400 to $25, and reducing the time it takes to process a portfolio from six to eight weeks to 48 hours". But not only have these platforms shown to reduce costs by 90%, increase efficiencies by 20x, and achieve over 90% accuracy, they primarily allow companies to make quicker and more informed decisions enabling their money to start working for them in a shorter timeframe.

Until next time, I hope you enjoyed the read. GB

Hashtags

#AI #ArtificialIntelligence #DataScience #MachineLearning #ML #Ethics #Data #DocumentIntelligence #OCR #NLP #NPL #Finance

References

Datamation. (2017). “ Unstructured Data ”. Available at: https://www.datamation.com/big-data/unstructured-data . [Accessed 21 April 2022]
Forbes. (2022). “ Leading Founders Of Fast-Growing Companies Share Three Tenets Of Success ”. Available at: https://www.forbes.com/sites/benjaminlaker/2022/04/19/founders-of-fast-growing-companies-share-three-tenets-of-success/ . [Accessed 21 April 2022]
International Banker. (2021). “ TACKLING NON-PERFORMING LOANS IN A PERFORMING ECONOMY ”. Available at: https://internationalbanker.com/banking/tackling-non-performing-loans-in-a-performing-economy/ . [Accessed 21 April 2022]
Investopedia. (2021). " Nonperforming Loan (NPL) ". Available at: https://www.investopedia.com/terms/n/nonperformingloan.asp . [Accessed 21 April 2022]
Semrush. (2021). “ 65 Artificial Intelligence Statistics for 2021 and Beyond ”. Available at: https://www.semrush.com/blog/artificial-intelligence-stats/ . [Accessed 21 April 2022]
Think Evolve Solve. (2021). “ CHALLENGES ORGANISATIONS FACE IN BECOMING DATA-DRIVEN" . Available at: https://thinkevolvesolve.ie/challenges-organisations-face-in-becoming-data-driven/ . [Accessed 8 March 2022]

The Analytics Summit 2021 Trends - Data, Sustainability & Ethics

Wed, 01 Dec 2021 13:24:22 GMT

4 Minute Read - Last week I attended the virtual/in-person Analytics Summit 2021 Conference and it was great to see the opportunities for data towards sustainable growth that have emerged due to almost two years of a pandemic. There were a couple of running trends apparent throughout all of the talks, and below I have outlined some of my takeaway points from the day of informative and inspiring talks. All thoughts and views are my own.

Data-Driven

One thing that data-driven companies have in common is that they have proven time and time again to be more resilient, with a recent study showing that 82% of data-driven companies have reported critical business advantages during the pandemic (Tableau, 2021). But in the drive to become a data-driven company (i.e. 85% of businesses want to be data-driven), only 37% of businesses are successful (Tableau, 2021). The reason for this low percentage is that not only are there a number of challenges when it comes to data collection and usage, some of which I outlined in one of my previous articles, ‘ Industry Future of AI for Health and Wellness ’, but also not enough emphasis put on business outcomes as a result of using the data. Dr. Matthew Howard, International Lead, Public Sector Healthcare Data Science and AI at AWS, outlined his formula for businesses to have the most effective harnessing of data:

(Mindset + People + Process) * Technology

Sustainability

Recently, more and more emphasis has been put on global sustainability progress to prevent our future generations from inequity and climate related crises. Sustainable AI was a key trend running across almost all of the talks. One interesting project that was mentioned was Terrain-AI (Terrain-AI, 2021), a jointly funded €5m climate change project between Science Foundation Ireland (SFI) and Microsoft which aims to help understand the impact of human activity on land use. Trevor Dhu, Asia Lead, Sustainability Science at Microsoft started with a powerful message saying that “ we need to go faster to drive towards a sustainable world ”. But the interesting point to this project was that while collecting and analysing the data, they identified another potential use-case. When analysing the terrain imagery, they realised that they were able to recognise areas of habitat, and as a result, identify areas that would be in need for future electric vehicle charging stations. I thought this was a really good example of being able to apply data to solve a different problem.

Trust & Ethics

I have written a number of articles touching and focusing on ethical AI including “ Are Humans the Next Horse? The Rise of the Robots ” and also the start of my 3-part series “ The Rise of Ethics in Artificial Intelligence (Part 1: Privacy) ”, and again this seemed like an important topic of interest throughout the discussions. During the EY panel discussion on data and trust, it was noted that there has recently been a shift of trust from mainly being focused on regulatory and compliance to becoming the centre of attention and playing a more crucial role in the developments and future of business strategy. There was a major emphasis put on the importance of building intelligent trust at the forefront of design in order to strengthen investor confidence and also manage risk. When building AI solutions, we need to ensure that we embed human values, collaborate towards the responsible advancement of AI, and also create transparency through education.

Final Thoughts

It’s clear to see the importance of not only having accessible data but also the ability to analyze and provide intelligence as a result of this data. A recent report by Gartner states that 97% of data sits unused in organizations (AWS, 2020), and from the data that is used, the majority of a data scientist’s time (i.e. 80%) is spent on finding, cleaning, and reorganizing the data (Info World, 2017). Business leaders within companies need to be aware of and understand the value that is possible when their data is considered as a central part of their strategy.

Within Altada, we are developing cutting-edge AI solutions that enable companies to unlock the value in their data, enhance their automation capabilities, and enable the implementation of data-driven decision making. Working with asset managers, multi-family offices, and institutional investors to name but a few across industries such as financial services, travel, healthcare, and security, we have helped our clients gain a competitive advantage in areas such as document intelligence and regulatory compliance. Want to know more? Make sure to get in touch.

Until next time, I hope you enjoyed the read. GB.

Hashtags

#AI #ArtificialIntelligence #DataScience #MachineLearning #ML #Trustworthy #Ethics #Policy #Regulations #Sustainability #Data #DecisionMaking #DocumentIntelligence #DueDiligence #Compliance

References

Info World. (2017). “The 80/20 data science dilemma”. Available at: https://www.infoworld.com/article/3228245/the-80-20-data-science-dilemma.html . [Accessed 27th November 2021]
Tableau. (2021). “5 key shifts for successful data-driven decision making”. Available at: https://www.tableau.com/en-gb/about/blog/2021/8/5-key-shifts-successful-data-driven-decision-making . [Accessed 27th November 2021]
Terrain-AI. (2021). “Terrain-AI: Uncovering new insights to support effective climate change decision making”. Available at: https://terrainai.com/ . [Accessed 27th November 2021]

Industry Future of AI for Health and Wellness

Tue, 07 Sep 2021 11:26:09 GMT

8 Minute Read - Last Friday, I had the pleasure of speaking at The International John McCarthy AI Summer School Conference hosted by the RDI Hub. During a panel discussion on the “Future of AI for Health and Wellness in Industry in the Short, Medium, and Long Term”, I got the opportunity to discuss how AI is currently being utilised within healthcare, some of the challenges that are being faced within the industry, and also some of the future trends. For those of you who couldn’t join, I put together a quick overview of some of the areas I covered during the discussion.

AI Benefits to the Pharmaceutical Lifecycle

Drug Discovery

One of the main challenges when attempting to discover new treatments is that it's becoming increasingly expensive and competitive with a greater emphasis being put on safety. In Japan, it is said that only 1 in around 30,000 drug discovery projects result in a successful launch (Nippon Shinyaku, 2020). This gives fantastic opportunity to apply AI during the drug discovery phase to add benefits such as:

Reducing R&D costs while avoiding costly errors, resulting in making drugs more affordable. There is huge savings to be made here as it's said that the cost of discovering and developing a new drug is as high as $2.5 billion dollars (DiMasi et al., 2016).
Predicting the success rates based on initial screening of drug compounds, as it’s said that only one out of ten molecules entering the trial phase will get successful clearance (Hay et al., 2014).
Tackling a range of complex problems that are difficult without the advancements in technology. One example of this is AlphaFold; a solution produced by DeepMind that solved a 50 year old biological challenge to understand how protein folds (DeepMind, 2020). As a result, it has also paved the way to understand how to create designer medicines, develop highly nutritious crops, and also create specific enzymes that can break down plastic pollution (The Guardian, 2020).

Clinical Trials

The clinical trials then help to identify any risks or errors that may become apparent during consumer use. A recent survey by MIT found that less than 14% of drugs successfully pass clinical trials (Oxford Academic, 2019). This creates opportunity to apply AI to produce the following benefits:

The quick analysis and identification of the best patient for particular trials based on various factors such as their medical history, current disease conditions, demographics, and ethnicity. One example of this is IBM Watson for Clinical Trail Matching, which improves the candidate selection process and helps ensure uptake by providing trial opportunities to most suitable candidates (IBM Media Center, 2020).
The repurposing of drugs by helping to identify molecules that may have failed but can be applied to target other diseases (Prasad, K., & Kumar, V., 2021).

Distribution / Supply Chain

One of the challenges when it comes to distribution is the identification of the quickest and most cost-effective means to transport the goods. By implementing AI across the different pillars of distribution, it allows for the end-to-end visibility to monitor, predict, and manage all aspects of the supply chain (Pharma Manufacturing, 2019) adding benefits such as:

Demand forecasting: to forecast and automatically adjust inventory levels to prevent over-demand and under-demand. It is said that by using AI during forecasting, errors can be reduced by up to 50%, warehousing costs can be reduced by up to 40%, and also lost-sales can be reduced by up to 60% (McKinsey Digital, 2017).
Transport logistics: to understand availability, transport capacity, transport lead times, real-time decisions for delays, and re-routing options if required due to disruptions. By taking advantage of AI, savings towards 71% can be generated in terms of time, distance, and fuel expenses (Medium, 2019).
Predictive maintenance: to provide insights into operations and equipment performance in order to keep machine uptime at the highest possible. A recent survey by McKinsey stated that manufacturing machine downtime can be reduced by 50% and machine life can be increased by 40% by using predictive maintenance (McKinsey, 2017).
Warehouse automation: to increase productivity, improve accuracy, and also increase safety.

Patient / Data

Currently, one of the most common use cases of AI in healthcare systems is in the early detection and also the accurate diagnosis of diseases based on medical imagery. One of the biggest challenges and goals when it comes to diagnoses is to increase the accuracy. AI allows for a more data-driven approach to compliment and augment a physician in making a more informed and calculated diagnosis. An example of this is from Researchers at Houston Methodist Research Institute in Texas; where they have developed AI technology that show patient data translated into diagnostic information 30 times faster than a human doctor, with 99% accuracy (Wired, 2016). In recent years, the results of these collaborations have improved to the point that the FDA have already approved a number of AI platforms that have resulted in a number of advantageous outcomes such as the identification of brain bleeding on CT scans (Arbabshirani, M. R. et al, 2018) and the recognition of abnormal heart rhythms from an Apple Watch data (Tech Crunch, 2017).

Industry Challenges for AI Adoption

Within industry, AI has started to become a critical component in the future direction and strategic objectives, with a recent survey showing that over 50% of global healthcare companies will implement an AI strategy by 2025 (Pharma News Intelligence, 2021). But for these strategies to be successful within industry, I see three main challenges that need to be overcome.

Business Value and Business Use-Case Identification

The challenge here is that most companies limit the implementation of AI to a small impact part of the business and therefore the return of investment is relatively small. This ‘playing it safe’ results in them generally not being able to see the future potential returns. The solution for this is that companies need to be willing to invest and prioritise AI in areas that are suitable for longer term goals and strategies.

Skills and Expertise

The challenge here is that not only do most industries not know what technical challenges are involved for the implementation of AI into their processes/projects, it can also be hard to find the right resource with the right background. The solution here is to constantly up-skill and educate employees to the point where you have technical leaders that are leading the technical decisions and direction within the company. In my previous article “ Rethinking Talent to Thrive In An Agile AI World ”, I outlined the impact of AI on the job market, how to make Ireland a recruitment magnet for experts, and also how to attract more women into AI-related roles.

Data

The challenge here is around access to large volumes of data, the appropriate collection of data, the structure and labelling of data, and also the accuracy/quality of that data. In the majority of cases, this type of data is not readily available, possibly due to range of factors such as mergers and acquisitions, poor data management processes, and restricted access to data. The solution here is that companies need to understand their current data acquisition processes and also implement efficient techniques and process to obtain larger amounts of data.

Long Term Trends for AI in Healthcare

Pandemic Response

If the last 18 months have thought us anything it’s that life can be unpredictable. We need to have innovation practices in place to be able to react and adapt quickly to these changes. The ability to constantly increase the efficiencies across the entire lifecycle is going to be crucial to reduce the time to market for new drugs. We have seen it take 300 days from identifying the coronavirus genome to the first vaccine study, which has previously taken an average of eight to ten years (Forbes, 2020). The advancements that we make, such as the ones outlined above, will allow new medicine delivery times to be short and available to the consumer under short time periods.

Predictive Healthcare

For the majority, people generally wait until they become sick before they go to see the doctor, and in many cases, wasting their own time and the time of the medical professional. Now with mainstream access to fitness devices, and as we move towards chip implants and ingestible sensors that can continuously monitor blood pressure/blood sugar levels and other vitals, people will start to become more informed about their health and be notified on anomalies and when they will need to see a doctor (predictive maintenance for your body).

Precision Medicines

Most of us when we are sick, walk in into the pharmacy and pick up one of the many options of either branded or generic drugs (89% of all which were present in all prescriptions dispensed in the U.S. last year (Accessible Meds, 2020)), and hope that they work well enough to get us back on track. Precision and personalised medicines has been on the increase in recent years, and will also continue to rise. The ability to combine information from previous diagnosis and scans, and base predictions on historical health issues from a person’s genomes, resulting in personalised treatment plans, will become more common.

Final Thoughts

As we move towards a world where almost all straight-forward, and in some cases quite complex, manual tasks have been automated, it will be more and more important to place our trust in these advancements. Not only with ethics play a huge role in this (I’ve also written a 3-part series on this – starting with “ The Rise of Ethics in Artificial Intelligence (Part 1: Privacy) ”), but also explainable AI (the transparency around the decision making process). There is fantastic work being done in this by Urja Pawar from MTU in collaboration with McKesson (Pawar et al., 2020), and it’s these collaborations between industry, research centres, and universities that are going to pave the way to ensure that from an academic point of view, academia is aiming to tackle real-world business focuses problems, and from an industry point of view, processes are being put in place to allow for data-science projects to be carried out.

Hashtags

#Technology #Tech #AI #ArtificialIntelligence #DataScience #ML #MachineLearning #Health #Wellness #AIHealth #AIWellness #AISS

References

Accessible Meds. (2020). The Generic Drug Supply Chain . Available at: https://accessiblemeds.org/resources/blog/generic-drug-supply-chain . [Accessed 4 September 2021].
Arbabshirani, M.R., Fornwalt, B.K., Mongelluzzo, G.J. et al. (2018). Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration , Digital Med, Volume 1, Article 9. Available at: https://www.nature.com/articles/s41746-017-0015-Z . [Accessed 4 September 2021].
DeepMind. (2020). AlphaFold: a solution to a 50-year-old grand challenge in biology . Available at: https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology . [Accessed 2 September 2021].
DiMasi, J. A., Grabowski, H. G., & Hansen, R. W. (2016). Innovation in the pharmaceutical industry: new estimates of R&D costs . Journal of health economics, Volume 47, Pages 20-33. Available at: https://pubmed.ncbi.nlm.nih.gov/26928437/ . [Accessed 3 September 2021].
Forbes. (2020). The Increasing Use Of AI In The Pharmaceutical Industry . Available at: https://www.forbes.com/sites/cognitiveworld/2020/12/26/the-increasing-use-of-ai-in-the-pharmaceutical-industry . [Accessed 5 September 2021].
Hay, M., Thomas, D. W., Craighead, J. L., Economides, C., & Rosenthal, J. (2014). Clinical development success rates for investigational drugs . Nat Biotechnol, Volume 32, Pages 40-51. Available at: https://pubmed.ncbi.nlm.nih.gov/24406927/ . [Accessed 3 September 2021].
McKinsey. (2017). Manufacturing: Analytics unleashes productivity and profitability . Available at: https://www.mckinsey.com/business-functions/operations/our-insights/manufacturing-analytics-unleashes-productivity-and-profitability . [Accessed 5 September 2021].
McKinsey Digital. (2017). Smartening up with Artificial Intelligence (AI) – What’s in it for Germany and its Industrial Sector? . Available at: https://www.mckinsey.com/~/media/McKinsey/Industries/Semiconductors/Our%20Insights/Smartening%20up%20with%20artificial%20intelligence/Smartening-up-with-artificial-intelligence.ashx%20str%209 . [Accessed 5 September 2021].
Medium. (2019). AI as the Ultimate Disruptor in Logistics: How to Manage Last-Mile Costs? Available at: https://medium.com/@ODSC/ai-as-the-ultimate-disrupter-in-logistics-how-to-manage-last-mile-costs-c4874e8f2ea0 . [Accessed 5 September 2021].
Nippon Shinyaku. (2020). About the Pharmaceutical Industry . Available at: https://www.nippon-shinyaku.co.jp/english/ir/Investor/pharmaceutical.php . [Accessed 4 September 2021].
Oxford Academic. (2019). Estimation of clinical trial success rates and related parameters . Biostatistics, Volume 20, Issue 2, Pages 273-286. Available at: https://academic.oup.com/biostatistics/article/20/2/273/4817524 . [Accessed September 3 2021].
Pawar, U., O’Shea, D., Rea, S., & O’Reilly, R. (2020). Incorporating Explainable Artificial Intelligence (XAI) to aid the Understanding of Machine Learning in the Healthcare Domain . Irish Conference on Artificial Intelligence and Cognitive Science, Pages 1-12. Available at: http://lucalongo.eu/aics2020/AICS2020_paper_62.pdf . [Accessed 5 September 2021].
Pharma News Intelligence. (2021). AI in the Pharma Industry: Current Uses, Best Cases, Digital Future . Available at: https://pharmanewsintel.com/news/ai-in-the-pharma-industry-current-uses-best-cases-digital-future . [Accessed 5 September 2021]
Prasad, K., & Kumar, V. (2021). Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2 , Current Research in Pharmacology and Drug Discovery, Volume 2. Available at: https://www.sciencedirect.com/science/article/pii/S2590257121000298 . [Accessed 2 September 2021].
Tech Crunch. (2017). Recognition of abnormal heart rhythms from an Apple Watch data . Available at: https://techcrunch.com/2017/05/11/apples-watch-can-detect-an-abnormal-heart-rhythm-with-97-accuracy-ucsf-study-says/ [Accessed 5 September 2021].
The Guardian. (2020). DeepMind AI cracks 50-year-old problem of protein folding . Available at: https://www.theguardian.com/technology/2020/nov/30/deepmind-ai-cracks-50-year-old-problem-of-biology-research . [Accessed September 3 2021].
Wired. (2016). This AI software can tell if you're at risk from cancer before symptoms appear . Available at: https://www.wired.co.uk/article/cancer-risk-ai-mammograms . [Accessed 5 September 2021].

The Fascination of Language (Part 1: Who’s Thomas.... And Why is he Doubting?)

Wed, 09 Jun 2021 18:09:55 GMT

5 Minute Read - I’ve always been fascinated by language. For the lucky ones, it’s something that has been learned, and now comes so effortless, on our journey to becoming adults. I’m constantly fascinated by people who can speak multiple languages... and even more so towards people who can inject their own culture into conversations not in their native tongue. In this two-part language series, I’ll take a look at phrases, idioms and words, starting with commonly used phrases and the origin behind them. All thoughts and views are my own.

Eaves Dropping

We all know eaves dropping to mean secretly listening to another’s conversation, but what is the origin of this phrase? Well, I must admit, when I was younger, I originally thought that this phrase was ‘ears dropping’. To me that made sense as it was something to do with listening. It was only when I was talking to a friend of mine a long while ago, I realised the true meaning behind the phrase. When you delve into the literal description of the words, an eave is the part of the roof that overhangs the walls of a building. An eaves drop originally referred to the water that fell from the eaves of a building, and later referred to the location on the ground to where that water fell. In medieval times, there was a legal restriction on buildings to have a perimeter around the eaves so the water falling would not destroy the neighbour’s property. Some people used to congregate within this perimeter under the eaves in order to listen to what was being said inside the walls. These people were described as eaves droppers.

Figure 1: Eavesdropping

Daylight Robbery

What seems like forever ago, I was travelling back from a Dublin conference in a taxi and I was met with the usual barrage of quick-wittiness, funny stories, and sarcasm that you would expect from a Dublin taxi driver. On this occasion, it was interspersed with some nuggets of historical knowledge; one being related to the old Georgian styled buildings we passed by and the size of their windows, and in some cases, bricked up windows. Back in the 1690s, William III introduced Window Tax in England which required people to pay tax based on the size of the windows and also how many windows they had in their building. This law was imposed on Ireland in 1799, before finally being repealed in 1851 (The Irish Times, 2000). As a way to combat the law, buildings started to reduce the size of their windows and even started to brick them up. Some of the older traditional Irish rural homes started to build half-doors as a way to let light in by opening the top half and keeping their animals out by closing the bottom half. As a result of this reduced daylight, the term “Daylight Robbery” was coined.

Figure 2: Bricked-Up Windows

Nip it in the Bud

Another one I used to get wrong… please tell me I’m not the only one. I was more anatomical in my expression of “Nip it in the butt”, but this time it has nothing to do with anatomy. Meaning to put an end to something before it gets worse, this phrase is referenced from horticulture where cutting a bud from a plant prevents the bud from blossoming into a flower or fruit. Although in saying this, some plants thrive when their buds are trimmed correctly, so a more aligned metaphorical meaning to “nip it in the bud” could be to end something sooner to get a better outcome.

Figure 3: Nip it in the Bud

Moaning Michael

Now before we move onto Thomas, we’ll take a short stop at Michael. Unfortunately, this isn’t too exciting and the only thing I could find on this is that we generally just like to alliterate and rhyme adjectives with given names (e.g. Skinny Minnie, Silly Billy). If you’ve heard of this phrase and don’t know where you heard it from, it could be from Father Noel Furlong (played by Graham Norton) in Father Ted.

Video 1: Father Ted

Doubting Thomas

I think one of the reasons I’m such a positive person is because as a child, my mother would tell me to believe in and never doubt myself like Thomas did. I used to think that Thomas must be the most pessimistic person, but who is he and what can we learn from him? Well in general, the phrase “Doubting Thomas” is used to describe someone who is skeptical and fails to believe until they have experienced it for themselves. The term dates back to and has religious connotations to Thomas the Apostle who failed to believe the resurrection of Jesus until he witnessed the wounds himself.

But is doubting such a bad thing? In a 2007 article at America Magazine, Gerald M. Fagin, associate professor of theology at Loyola University, argues that “doubters like Thomas can be great teachers if they prompt us to examine our own faith” (America Magazine, 2007). But on the other side, sometimes doubt can disable your ability to believe even when you are in an environment full of people you trust.

Figure 4: Doubting Thomas

Final Thoughts

When you think about communication through language, it’s incredible how we have evolved to interact with each other in a legible way. The addition of technology has enabled us to converse and discuss thoughts, emotions, and opportunities in real-time with people from different parts of the world. No one has all the answers and there will always be elements that we will never understand. Having that small bit of doubt in order to raise questions or voice concern until you are comfortable with all the facts, is a good thing. While we continue to get comfortable being uncomfortable, and hopefully returning to some sort of normality, it’s important to stay positive, stay focused, and stay kind. If we’ve ever needed that sense of community and working together, it’s now.

What are some phrases that you like and the origin behind them?

References

America Magazine. (2007). A Doubter Gives Lessons in Faith. [online] Available at: https://www.americamagazine.org/issue/633/faith-focus/doubter-gives-lessons-faith/ [Accessed 02 February 2021]
Figure Cover. (2019). Inclusive Language Guide. [online] Available at: https://counseling.northwestern.edu/blog/inclusive-language-guide/ . [Accessed 02 February 2021]
Figure 1: Eavesdropping. Mental Floss. (2013). How Eavesdropping Was Punished in Medieval Times. [online] Available at: https://www.mentalfloss.com/article/51282/how-eavesdropping-was-punished-medieval-times . [Accessed 02 February 2021]
Figure 2: Bricked-Up Windows. Wikipedia. (2021). Window tax. [online] Available at: https://en.wikipedia.org/wiki/Window_tax . [Accessed 02 February 2021]
Figure 3: Nip it in the Bud. Medium. (2019). Preparation Prevents Paralysis. [online] Available at: https://medium.com/the-book-mechanic/preparation-prevents-paralysis-d9df411de129 . [Accessed 02 February 2021]
Figure 4: Doubting Thomas. (2020). Is it Fair to Call Today’s Saint “Doubting Thomas?”. [online] Available at: https://catholicexchange.com/is-it-fair-to-call-todays-saint-doubting-thomas/ [Accessed 02 February 2021]
The Irish Times. (2000). Windows of opportunity. [online] Available at: https://www.irishtimes.com/life-and-style/homes-and-property/windows-of-opportunity-1.236073 . [Accessed 02 February 2021]
Video 1: Father Ted. (2013). Who’s a bit of a Moaning Michael tonight!
. [online] Available at: https://www.youtube.com/watch?v=YP5t5rdRoN0
. [Accessed 02 February 2021]

Rethinking Talent to Thrive In An Agile AI World

Tue, 01 Jun 2021 17:32:58 GMT

9 Minute Read - A few weeks ago, I had the pleasure of speaking at the AI Summit 2021. During a panel discussion on “Rethinking Talent to Thrive in an Agile AI World” I got the opportunity to discuss the impact of AI on the job market, how we can make Ireland a recruitment magnet for overseas AI-skilled executives, how we can attract more women into AI-related roles, and how we can use AI to attract and retain more talent. For those of you who couldn’t join, I put together a quick overview of some of the areas above that were covered.

AI Impact on the Job Market

Impact

In one of my previous articles “ Are Humans the Next Horse? The Rise of the Robots ”, I took a look at the impact of the previous industrial revolutions. During these revolutions, people were worried about losing jobs and fearful about loss of freedom and autonomy to boredom and repetition. Although jobs were lost, for the majority, each advancement brought a better quality of life and also resulted in a broader range of jobs. But this time around it’s slightly different, and depending on what report you read or what expert you listen to, we could be on the cusp of our own extinction.

Ethics

One approach aimed at combatting these fears of self-destruction is to ensure that ethics is introduced at the forefront. I discussed this is more detail during my previous article “ The Rise of Ethics in Artificial Intelligence (Part 3: Trustworthy AI) ”, explaining how AI is becoming more of a humanities problem than an technology problem as we aim to ensure that the technical solutions created using AI will have a positive effect on the health, well-being, and future of human kind. The trust of these solutions is still a major concern, especially within the healthcare industry. One concept that aims to help create transparency is Explainable AI, which aims to unravel the black block of decision making to allow the user to understand the process, the models that were used to train the algorithms, and also validate the result. There are great advancements being made from MTU (Munster Technological University) around understanding the hierarchical nature of medical workflows (Pawar, U., et al, 2021).

Soft-Skills

In relation to the job market, we are going to see a big emphasis on soft-skills with people being encouraged to adapt and develop soft skills such as empathy, creativity, curiosity, and emotion, to complement their technical skills. People will need to start considering what skills and capabilities they should develop to ensure they are employable for future jobs. Jobs that solely rely on low-level repetitive and tedious tasks will most likely be displaced due to the advancements in technologies, but it will also alleviate humans to focus on more higher-level functions and meaningful tasks - the soft skills of today will be the hard skills of tomorrow. This will obviously create a demand for new and different types of jobs such as ethical officers to ensure that AI is introduced correctly in adherence to company goals and values, walker/talkers to enable us to become more human again as more and more jobs become automated, mental health officers to deal with the unknown impact of human and machine interaction on a daily basis, and financial coaches when cash is obsolete as digital currency and automated loans and payments become more and more common.

Rethinking Education

Due to the need for this soft-skills shift in addition to the ever increasing importance and value of AI, we have started to see universities creating new AI curriculums, with CIT / MTU creating Ireland’s first MSc in Artificial Intelligence back in 2018 (Silicon Republic, 2018). These curriculums are then complimented by Skillnet who provide access to funded courses and also work with industry to identify future required business skills ensuring that courses are addressing these requirements. As the importance of these soft-skills that will augment the boundaries of technology and human interaction continue to increase, we also need to see the early learning education system evolve from a predominantly focused left-brain (analytical, methodical) curriculum to right-brain curriculum (creativity), enabling and allowing kids to flourish in their creative elements and equipping them with the future required skills for employment.

Making Ireland a Recruitment Magnet for Overseas AI Executives

High Profile Experts

For Ireland to continue to be a leading tech hub for start-ups and innovators (Talent Garden, 2020) and keep the highest ratio of AI talent in the European Union (The Irish Times, 2019a), we need to consistently attract expert talent. Smart people want to work with smart people, so having experts well renowned in their fields will help attract more talent. It’s important to constantly get people like Professor Aljosa Smolic, SFI Research Professor of Creative Technologies at Trinity College Dublin who has worked on numerous R&D projects and publications (Smolic, Prof. Aljosa., 2021), involved with industry and start-ups to share their experiences, knowledge, and lessons learned.

Headhunting

But we shouldn’t wait for these experts to find opportunities, we should also proactively target talent with opportunities. Companies such as Alldus (Alldus, 2021), who are AI, data, and technology recruitment specialists, are taking a holistic approach to doing this by working with clients to build communities of experts, understand their requirements, and then connect them to the best people in AI.

Promote Ireland

This task is helped by the fact that Ireland is a key location when it comes to attracting top talent. Ireland is ranked 12th in the world on the Global Peace Index of the top safest countries to live (Statistics Times, 2020) and ranked 2nd in the world on the United Nations study for the quality of the life (The Irish Post, 2020). The education system in Ireland is world renowned for young people having the highest levels of education in Europe and 4th highest in the world (The Irish Times, 2019b). And if that wasn’t good enough, just to sweeten the deal, there are fantastic government incentives towards R&D which allow the possibility of obtaining up to 50% in tax credits for R&D initiatives (Enterprise Ireland, 2021).

Showcasing Projects

To finish it off, it’s also important to have AI conferences and awards such as the AI Summit (AI Summit, 2021) and AI Awards (AI Awards, 2021) to showcase the amazing work that is being done in Ireland.

Attracting More Women into AI-Related Roles

It’s very clear to see that there’s a gender gap when it comes to AI, with recent reports (World Economic Forum, 2019) showing less that 30% of professionals in data and AI are women, and will remain with a gap for the next 100 years.

Role Models

One way we can aim to continuously reduce this gap is to have more female role models. One of the major challenges is that some people still view and have the perception that technology and AI is a ‘male-only’ career path, so we need more role models like Dr. Begüm Genç, Postdoctoral Researcher at Confirm Centre (Genç, Dr. Begüm, 2021) and Alessandra Sala, Director of Artificial Intelligence and Data Science at Shutterstock (Sala, Alessandra, 2021) to pave the way and share their experiences in the AI industry by highlighting the benefits and opportunities of working within technology.

We are constantly seeing progress in this area. A good example of this is back in April of this year, Professor Linda Doyle, who is an advocate for the arts and women in STEM, was announced as the first woman to be elected as provost in Trinity College’s 429-year history (Silicon Republic, 2021). TD Simon Harris reacted to this saying that this means “another glass ceiling has been shattered”. We all need to keep shattering those glass ceilings.

Environment that Welcomes Diversity

Another thing we can do is to consistently create environments that welcome and celebrate diversity. There’s been a big increase in companies focusing and creating metrics around diversity and inclusion, and with the recent changes in the workplace, the introduction of more flexibility within people’s roles will also help. We’re also seeing companies like McKesson partnering with universities (i.e. MTU) and research centres (i.e. SFI ADVANCE) to create PhD scholarship programmes. During this process, we saw a 700% increase in the number of female PhD applicants based on the neutral branding and marketing of the position, due to the fact that women generally don’t apply for roles unless they meet a larger percentage of the criteria of the requirements, and generally underrepresent themselves in a factor of 3 to 1 when applying for roles and positions (Harvard Business Review, 2014).

Using AI to Attract Talent

Talent Management Core Challenges

One of the biggest challenges in talent management is helping employees develop and progress within the organisation. 78% of employees feel that it’s up to the employer to provide the environment for them to up-skill and grow within their career (Forbes, 2020). The following are some of the core challenges of talent management (Work Trends, 2020):

Personalisation: We are all too accustomed to having information on-demand, so if we don’t see what we want, whether it be a job opportunity or development plan, we give up and move on.
Candidates Time: A lot of time is spent sifting through potential candidates, and only a very small portion of them are ever successful. Furthermore, once the candidates have gone through the process, whether successful or unsuccessful, more often than not they are removed from the internal databases or systems.
Lack of Skills Visibility: Most companies don’t have any idea or overview of the skills and capabilities that exist within their organisation. For the most part, if an inventory is taken, it is only a snapshot in time and doesn’t take account of previous employees or have a consistent way to retrieve this information on a regular basis.
Future of Work: If companies don’t have this up to date inventory, then it’s not possible to know the potential of what can be achieved. In addition, sometimes companies themselves don’t have a good handle on what skills are required to do each of their jobs.
Diversity: It’s proven that a diverse workforce outperforms a non-diverse workforce by allowing for greater creativity, greater ideas, and greater innovation. One company that is actively working on increasing the diversity that joins your company is The Context Factory who are deploying their ethical machine learning technology during the hiring process (The Context Factory, 2021).

AI Towards Talent Intelligence

By introducing AI into your talent management system, some of the core challenges outlined above can be addressed. If companies have a good grasp and understanding of their employees and what their capabilities are, they can start to see patterns on what type of people in relation to their background and skills perform well for specific roles and tasks. This then creates an opportunity to infer missing potential information from a candidates profile to bring people into the company that may be from unconventional and diverse backgrounds, enabling a level playing field (i.e. people are not considered based on key words from their resume, but based on what the AI knows should exist based on the data).

Retaining Talent

In addition to personalising job recommendations to both external and internal candidates, once candidates are successful in securing a position, AI can be used to introduce personalised training and development plans, suggest projects to get involved with to build up certain skills or utilise and make the best use of the candidates, and also highlight the impact of different perspectives across the organisation.

Final Thoughts

As AI is introduced more and more to replace manual tasks, people will need to understand how they can complement this technology and become valuable assets in the cohesion between technology and human interactions. More emphasis should be put on the cost and impact of education towards our future workforce and the required skills that will keep humans on the cusp of innovation. We’ve seen the economy go through turmoil during the last year, and it’s only when companies have a really good overview of their capabilities within their organisation, a breakdown of their projects and requirements, and the skills that are required to continue to perform and be profitable, that they’ll be able to transform rapidly during these uncertain times. As we continue to progress towards a technological future with AI replacing more and more tasks, we need to continue to grasp onto what truly makes us human, and provide people with opportunities to utilize their talent and harmonize with technology resulting in the ultimate combination.

Hashtags

#ai #artificialintelligence #innovation #machinelearning #recruitment #agile #talent #futureofwork #talentacquisiton #hr

References

AI Awards. (2021). AI Awards – Connecting Ireland’s AI ecosystem for a higher purpose. Available at: https://aiawards.ie/ . [Accessed 27 May 2021].
AI Summit. (2021). Embrace the AI opportunity today with a best practice implementation strategy. Available at: https://aisummit.ie/ . [Accessed 27 May 2021].
Alldus. (2021). Alldus – Leaders in AI Staffing. Available at: https://alldus.com/ie/ . [Accessed 27 May 2021].
The Context Factory. (2021). Whole Village Hiring. Available at: https://thecontextfactory.com/ . [Accessed 1 Jun 2021]
Enterprise Ireland. (2021). Research, Development & Innovation (RD&I) Fund. Available at: https://www.enterprise-ireland.com/en/funding-supports/Company/Esetablish-SME-Funding/R-D-Fund-Large-Projects-.html . [Accessed 27 May 2021].
Forbes. (2020). Accenture Research Shows Employees Care About Much More Than Money – Here’s What They Need To Build Your Business. Available at: https://www.forbes.com/sites/nelldebevoise/2020/10/08/your-employees-dont-care-about-money--heres-what-they-need-to-build-your-business/?sh=7d00b81e1645 . [Accessed 1 Jun 2021]
Genç, Dr. Begüm. (2021). Dr. Begüm Genç. Available at: http://www.cs.ucc.ie/~bg6/ . [Accessed 27 May 2021].
Harvard Business Review. (2014). Why Women Don’t Apply for Jobs Unless They’re 100% Qualified. Available at: https://hbr.org/2014/08/why-women-dont-apply-for-jobs-unless-theyre-100-qualified . [Accessed 27 May 2021].
The Irish Post. (2020). Ireland has second-highest quality of life in the world, according to UN report. Available at: https://www.irishpost.com/news/ireland-has-second-highest-quality-of-life-in-the-world-according-to-un-report-200228 . [Accessed 27 May 2021].
The Irish Times. (2019a). Ireland is top AI talent hub in the EU. Available at: https://www.irishtimes.com/business/technology/ireland-is-top-ai-talent-hub-in-the-eu-1.4096841 . [Accessed 27 May 2021].
The Irish Times. (2019b). Young people in Ireland among world’s most educated. Available at: https://www.irishtimes.com/news/social-affairs/young-people-in-ireland-among-world-s-most-educated-1.4013671 . [Accessed 27 May 2021].
Pawar, U., et al. (2021). Evaluating Hierarchical Medical Workflows using Feature Importance. Available at: https://www.researchgate.net/publication/350856053_Evaluating_Hierarchical_Medical_Workflows_using_Feature_Importance . [Accessed 27 May 2021].
Sala, Alessandra. (2021). Alessandra Sala. Available at: https://www.linkedin.com/in/salaalessandra . [Accessed 27 May 2021].
Silicon Republic. (2018). Ireland’s first master’s degree in AI driven by spectre of a skills shortage. Available at: https://www.siliconrepublic.com/careers/ai-masters-degree-ireland . [Accessed 27 May 2021].
Silicon Republic. (2021). Who is Linda Doyle, the newly elected provost of Trinity College Dublin? Available at: https://www.siliconrepublic.com/innovation/linda-doyle-provost-trinity-college-dublin . [Accessed 27 May 2021].
Smolic, Prof. Aljosa., (2021). Professor Aljosa Smolic. Available at: https://www.tcd.ie/creative-arts/staff/SMOLICA . [Accessed 27 May 2021].
Statistics Times. (2020). Global Peace Index. Available at: http://statisticstimes.com/ranking/global-peace-index.php . [Accessed 27 May 2021].
Talent Garden. (2020). Why Dublin is a Leading Tech Hub for Startups and innovators. Available at: https://talentgarden.org/en/digital-transformation/why-tech-startups-should-choose-dublin . [Accessed 27 May 2021].
Work Trends. (2020). Brad Sutton – How AI is Reinventing Talent Management. Available at: https://open.spotify.com/episode/4n3TxoVolMpmsuOdLwG7lB?si=JD5csAoBQqiEts0U5otFNQ . [Accessed 1 Jun 2021]
World Economic Forum. (2019). Global Gender Gap Report 2020. Available at: https://www.weforum.org/reports/gender-gap-2020-report-100-years-pay-equality . [Accessed 27 May 2021].

Topicgories - The The Music, Sport, and Screen Quiz App That Everyone is Talking About

Mon, 21 Dec 2020 18:12:50 GMT

In my previous two articles ( Numbagories and Pictagories ), I outlined the process of creating my first two personal mobile apps. This article outlines the 3rd app in my series of quiz apps. Topicgories is a FREE Android application where the aim is to solve music, sport, and tv/movie puzzles that are suitable for all ages and will have your mind boggled, your tongue twisted and your head rattled as you race against the clock to achieve those precious points. In this article, I will talk through how I expanded on my first two apps in order to create a brand new app. But in the meantime, please download and play along.

Name

When deciding on a name, I continued the same approach of my previous two apps; by settling on a name that was relevant, catchy and unique, and also having the social handles available. In the same way that Numbagories is related to numbers and Pictagories is related to pictures, Topicgories is related to quiz challenges for different topics (i.e. sport, music, and screen - tv/movies).

Reusability

After transforming my initial app and improving on the codebase in terms of quality, testing, and also reusability, I was able to reuse a lot of the features and functionality that was common across my series of apps.

Design

I think that design is something that can constantly evolve in order to improve over time. The more feedback you receive, the more you understand how users use your app. The more research you do on other apps, the more you learn about user psychology. All of which better equip yourself with the tools needed to create an app that delivers an impeccable user experience.

From Concept to Reality

I've been thinking of this app for a long long while now. Pictagories was very similar in terms of styling to Numbagories, so that was the natural next step. This app then built on the premise of providing different types of questions and allowing me to get creative in developing interesting ways to provide the challenges. Of all my apps, I'm most proud of this one as it combines a number of different image processing elements and has a number of creative ways to display the quiz questions.

Colour Palette

Inspiration can come from anywhere and in all shapes and sizes. I wanted to carry across some of the similar stylings and colours of my previous apps in order to make it feel like part of the same app family, but I also wanted to try and introduce a new complimentary primary colour into the mix. One of the days, I was walking past the L'Atitude 51 Wine Bar in Cork, as I have done on many occasions, but for some reason have never really noticed the colours. This time, possibly because I was looking for some colour inspiration, I noticed how nice the wine and cream colours complimented each other, along with the subtle grey in the stone work. This was exactly the colour scheme I was looking for, and tada, I had my colour scheme picked.

Logo

In continuation of the design flow for my previous apps, the logo followed suit. The logo that you see below, contains the first initial of the app name along with the name of the app underneath, and stays in line with the logo scheme for the series of apps. Looking at the logos of Numbagories, Pictagories, and Topicgories side by side, you automatically know that it's part of the same series of apps.

Gamification

They say 'don't fix it if it ain't broken'..... so I continued with the same achievements as my previous two apps. These achievements are split into 'In-Level Achievements' and also 'Evolution Achievements'. The in-level achievements are awarded while playing and completing a level with a specific focus on speed and accuracy. The evolution achievements are awarded for progression through the game. Both, in addition to achieving points for completing the levels, give the user a sense of completion, achievement, and also satisfaction. On each of the social media channels outlined below, throughout the course of the next few weeks, I will provide further information on each of these achievements and what needs to be done in order to be awarded them. I also have ideas on additional achievements I can add into later versions of the app, so watch this space.

Marketing

Once the app has been designed, developed, and tested, it was then time to publish to the store and market the app. The following are the steps that I've taken, and continuing to take, in order to market and brand the Topicgories app.

Domain and Social Media

In parallel to coming up with the name as outlined above, I secured the domain http://www.topicgories.com/ along with the handle @Topicgories for each of the major social media platforms.

Poster

Once I was happy with the design of the app, the next step was to create the poster. This poster is a good way to brand, provide an overview of what the app looks like, a quick description of what the app does, along with details of how to download, get in touch, and find out further information.

Intriguing Tagline

The next step was to create a tagline to compliment the poster. I chose this tagline to be similar to the style of Numbagories and Pictagories, again to strengthen the link between the series of apps and show they are all from the same family.

The next step was to create a tagline to compliment the poster. I chose this tagline to be similar to the style of Numbagories and Pictagories, again to strengthen the link between the series of apps and show they are all from the same family.

Website

Once the design, social media handles, poster, and additional information was complete, this can all be displayed on the website. The website is a good way to provide all the information to the user in a single interface.

Additional Information

At this point, everything is pretty much setup to allow people to find out information and download the app. The constant promotion and marketing of the app will be crucial in order to get more people to download, more feedback to improve, and more people invested in the series of apps. To complete the information, the following is the full text in relation to promoting Topicgories.

Topicgories is a FREE Android application where the aim is for you to solve the various puzzles on music, sport, and tv in order to earn points and achievements, evolve through the ranks, and complete the game. The quicker you solve the puzzles, the more points you will earn. Try and earn all the achievements to gain extra points.

Could you name the sport star from a pixelated image? Could you name the song from the opening lyric? Could you name the movie from a scene image? Then download one of the most exciting FREE apps that you will ever play RIGHT NOW…. This is guaranteed to keep you entertained for hours with its engaging puzzles.

Comprising of various brilliantly addictive levels, ranging in levels of difficulty, Topicgories is suitable for all ages and will have your mind boggled, your tongue twisted, and your head rattled as you race against the clock to achieve those precious points.

The aim is to solve the various different puzzles from each of the topics. The quicker you solve the puzzles, the more points you will earn. The more puzzles you solve, the more achievements you will earn. Try and earn all the achievements to gain extra points.

So what are you waiting for? Name that Topicgory!

◆ INSTANT FUN ◆ No intricate rules or registration. Just download and play now.

◆ ENGAGING AND ENJOYABLE BRAIN TEASERS FOR ALL AGES ◆ Ranging in levels of difficulty, this puzzle game caters for all ages, all levels of knowledge, and a game that the entire family can play.

◆ ADDICTIVE AND EXCITING PUZZLES ◆ Discover the answer to the various different puzzles. Can’t find the answer? Use the hints or share the level to play along with friends.

Everyone who is anyone is playing this game! Don’t be the only one left out. Download it NOW for FREE to play along.

Promotional Video

This is optional, and can take a bit of time, but it's a really nice way to compliment all the previous material and finalise the marketing with a professional feel. There are many different ways and styles to create a promotional video. The route that I've chosen is to combine all the material and screenshots into a 60 second clip that displays all the relevant information to the user.

Find Out More

Already a fan of Topicgories, then like and follow us on our social media channels to stay up to date with the latest news:

Instagram: https://www.instagram.com/ topicgories /
Facebook: https://www.facebook.com/ topicgories
Twitter: https://twitter.com/ topicgories
LinkedIn: https://www.linkedin.com/showcase/ topicgories

Pictagories - The Picture Quiz App That Everyone is Talking About

Mon, 26 Oct 2020 12:00:04 GMT

In my previous article ' Numbagories - The Number Quiz App that Everyone is Talking About ', I outlined the process of creating my first personal mobile app. This article outlines the 2nd app in my series of quiz apps. Following in the footsteps of Numbagories , Pictagories is a FREE Android application where the aim is for you to decipher the rebus puzzles, earn points and achievements, advance through the ranks, and complete the game. The quicker you solve the puzzles, the more points you will earn. In this article, I will talk through how I expanded on my initial app in order to create a brand new app. But in the meantime, please download and play along.

Name

As explained in the previous article, I had set up an extensible name scheme that can be used for my other app ideas. The same premise exists of being relevant, being catchy and unique, and having all social aspects free. In the same way that Numbagories was related to numbers, Pictagories is related to pictures.

Design

The same knowledge and design approach was applied to putting this mobile app together. The more you practice this approach, the easier it becomes, so it's important to find a process that works for you and stick to it.

From Concept to Reality

As a lot of the brainstorming work was already done with Numbagories, so I just needed to see how I could tweet a few bits to apply it to pictures. I wanted to keep the same look and feel, after all it is part of a series of apps, and I wanted the user to know and feel this when switching between and playing the apps. I followed almost identically the same process of Numbagories with the addition of a few tweaks to create the screens you see below.

Colour Palette

When deciding on a colour scheme, I wanted to carry across some of the same colours from Numbagories, again to make it feel part of the same app. I changed the main primary colour to blue in order to distinguish the app, but the other colours allow the seamless integration of Pictagories into the app quiz series. The colours that I have chosen for Pictagories is shown below, with the addition of some softer neutral colours that bring the colour scheme together.

Logo

In continuation of the design flow, the logo followed suit. The logo that you see below, contains the first initial of the app name along with the name of the app underneath, and stays in line with the logo scheme for the series of apps. Looking at the logos of both Numbagories and Pictagories side by side, you automatically know that it's part of the same series of apps.

Gamification

After getting some positive feedback in relation to the gamification elements of Numbagories, I decided to keep them for Pictagories. As with Numbagories, these were split into 'In-Level Achievements' and also 'Evolution Achievements'. The in-level achievements are awarded while playing and completing a level with a specific focus on speed and accuracy. The evolution achievements are awarded for progression through the game. Both, in addition to achieving points for completing the levels, give the user a sense of completion, achievement, and also satisfaction. On each of the social media channels outlined below, throughout the course of the next few weeks, I will provide further information on each of these achievements and what needs to be done in order to be awarded them.

Marketing

Domain and Social Media

In parallel to coming up with the name as outlined above, I secured the domain http://www.pictagories.com/ along with the handle @Pictagories for each of the major social media platforms.

Poster

Intriguing Tagline

The next step was to create a tagline to compliment the poster. I chose this tagline to be similar to the style of Numbagories, again to strengthen the link between the series of apps and show they are all from the same family.

Are you someone who likes to be challenged? Do you like to play word and picture games that will keep your mind guessing and your brain ticking? Then download one of the most exciting FREE apps that you will ever play RIGHT NOW…. This is guaranteed to keep you entertained for hours with its engaging puzzles and phrases.

Website

Additional Information

Pictagories is a FREE Android application where the aim is for you to decipher the rebus puzzles, earn points and achievements, advance through the ranks, and complete the game. The quicker you solve the puzzles, the more points you will earn. Try and earn all the achievements to gain extra points.

Are you someone who likes to be challenged? Do you like to play word and picture games that will keep your mind guessing and your brain ticking? Then download one of the most exciting FREE apps that you will ever play RIGHT NOW…. This is guaranteed to keep you entertained for hours with its engaging puzzles and phrases.

Comprising of 201 brilliantly addictive levels, ranging in levels of difficulty, Pictagories is suitable for all ages and will have your mind boggled, your tongue twisted, and your head rattled as you race against the clock to achieve those precious points.

The aim is to solve a collection of the most commonly used idioms, phrases, and objects. But it's not going to be easy. You will only be presented with an image representation of that common word or phrase. The quicker you solve the puzzles, the more points you will earn. The more puzzles you solve, the more achievements you will earn. Try and earn all the achievements to gain extra points.

So what are you waiting for? Name that Pictagory!

◆ INSTANT FUN ◆ No intricate rules or registration. Just download and play now.

◆ ENGAGING AND ENJOYABLE BRAIN TEASERS FOR ALL AGES ◆ Ranging in levels of difficulty, this puzzle game caters for all ages, all levels of knowledge, and is a game that the entire family can play.

◆ ADDICTIVE AND EXCITING PUZZLES ◆ Discover the link between the image and the common words and phrases to solve the puzzle. Can’t find the answer? Use the hints or share the level to play along with friends.

Everyone who is anyone is playing this game! Don’t be the only one left out. Download it NOW for FREE to play along.

Promotional Video

Find Out More

Already a fan of Pictagories, then like and follow us on our social media channels to stay up to date with the latest news:

Instagram: https://www.instagram.com/pictagories/
Facebook: https://www.facebook.com/pictagories
Twitter: https://twitter.com/pictagories
LinkedIn: https://www.linkedin.com/showcase/pictagories

Numbagories - The Number Quiz App That Everyone is Talking About

Mon, 19 Oct 2020 11:00:02 GMT

I’ve always been fascinated with creating something that others can play and enjoy. Ever since I got my first smartphone, I’ve always wanted to create a mobile app. During lockdown, I decided to continue this passion by developing and improving on my series of mobile apps. Over the next three articles, I’m going to explain my process of creation for each of them. I’ll start off with my first app that I created, Numbagories .

Numbagories, which is part of a series of quiz apps that I have developed, is a FREE Android application where the aim is for you to solve the number puzzles (e.g. 12 S of the Z => 12 Signs of the Zodiac), earn points, earn achievements, evolve through the ranks, and complete the game. The quicker you solve the puzzles, the more points you will earn. In this article, I break down the process of how I came up with the concept of the game, the process of improving the design and usability, adding gamification to the functionality, and also the marketing of the app. But in the meantime, please download and play along.

N ame

Not necessarily the very first step of the process, but it makes sense to start off with it here as I've been asked a good few times how I came up with the name. Well there were four main criteria I was looking for when trying to decide on the name of the app:

I wanted it to be relevant to the app itself - have some connection to the purpose of the app
I wanted it to be catchy and unique - a name (possibly made up) that people would have never heard of before
I wanted the possibility to extend the name to be part of a series - to use the same concept in order to expand to the other app ideas in the series
I wanted a name where the domain and handle for all major social media platforms were available

Sounds easy, right? Well it can be a little more trickier that you would think. After the initial step of brainstorming around the features and functionality, I had a discussion with a good friend of mine about the app. During the conversation, she had asked me to write down a couple of keywords related to the app. Two of those keywords were numbers and categories, which resulted in the 'Brangelina-ising' of the name Numbagories. From my perspective, this fit into each of the criteria I had previously mentioned above.... and tada, my app had a name. Personally, I think that once you place a name towards an idea it becomes a little more real. It makes it easier for you to visualise it coming together and also allows you to refer to it when thinking about the next steps; the next of which was to turn my brainstorming concepts into reality.

Design

A lot of work, careful consideration, iterative design and development, and testing goes into creating anything that people will use. There are a significant amount of important elements that need to come together coherently in order to create something tangible. Following some of the steps outlined in my previous article ' The Human-Centered Design Approach ' and also understanding the importance of this approach outlined in my previous article ' Why You Should Thank Leonardo da Vinci - An Overview of User Experience (UX) Design ', I began the journey of bringing my ideas to life.

From Concept to Reality

The brainstorming process for any idea is an extremely important one. It allows you to get all your ideas out onto paper, group them into similar areas, expand on them while thinking of the challenges, how people will interact, and also what people would be looking for, and also what it could potentially look like. This process is key in order to ensure that you've factored in all considerations which will ultimately save you a lot of time in the long run, as it is estimated the 50% of time is spent doing rework that could have been avoided (Usability.Gov, 2017) and that fixing an error after development is up to 100 times as expensive as it would have been before (Human Factors International, 2011).

Once all the thoughts have been laid out, I then worked on piecing them together into wireframe visualisations and behind the scenes functionality, which would ultimately form the basis of how the app would look and behave. The below shows the evolution of the wireframes, which I worked alongside a good friend of mine Cahail to help pull it together initially, which takes into account a number of other factors (e.g. colour scheme, usability, etc...) outlined in further sections of this article.

Colour Palette

When testing with users, it's important to initially focus on testing functionality, such as navigation controls, interaction with the flow, and information display. As the fidelity of the prototype increases, like the image above, you can start to introduce and test more metrics such as colour schemes, design, and visualisations.

W hen deciding on colour scheme, there is no one size fits all solution but there are a number of best practices that can be followed, one of which is the 60-30-10 rule (The Futur Academy, 2020). The first thing to do is to decide and organise your colour palette. This should be separated into your primary and secondary group colours along with your accent colour. The balance of colours here should follow loosely the rule outlined above, which will give your design consistency and purpose. When deciding on your colours, it's important to pick complimentary colours that work well together. The colours that I have chosen for Numbagories is shown below, with the addition of some softer neutral colours that bring the colour scheme together.

Logo

Sometimes we can overthink a logo. We look for something that looks amazing or funky or cool, but sometimes, the simplest are the best. Similar to the name above and my criteria outlined, I wanted to look for something that could be part of a series of apps and that by looking at them all side by side, you would know that they are all part of the same family. As a result of this, the following is the logo that contains the first initial of the app name along with the name underneath and a similar colour scheme in the background. This creates a clean and consistent feel that fits in with the app content and flow.

Gamification

In my previous article ' From stamps to a $5.5 billion industry - An Overview of Gamification ', I gave an overview of the importance and also potential when integrating gamification elements across many diverse sectors. I have chose to include a number of different achievements and rewards within the app in order to give the user satisfactions of completing the levels and give them something to aim for, on top of the joy they'll receive when successfully completing a level. I chose to split these out into 'In-Level Achievements' and also 'Evolution Achievements'. The in-level achievements are awarded while playing and completing a level with a specific focus on speed and accuracy. The evolution achievements are awarded for progression through the game. Both, in addition to achieving points for completing the levels, give the user a sense of completion, achievement, and also satisfaction. On each of the social media channels outlined below, throughout the course of the next few weeks, I will provide further information on each of these achievements and what needs to be done in order to be awarded them.

Marketing

Once the app has been designed, developed, and tested, it's time to publish to the store and market the app. The following are the steps that I've taken, and continuing to take, in order to market and brand the Numbagories app.

Domain and Social Media

In parallel to coming up with the name as outlined above, I secured the domain http://www.numbagories.com/ along with the handle @Numbagories for each of the major social media platforms.

Poster

Once I was happy with the design of the app, a poster was a good way to visually represent the app. This should be branded, provide an overview of what your app looks like, a quick description of what the app does, along with details of how to download, get in touch, and find out further information.

Intriguing Tagline

As the poster is only aimed at giving people an overview, it's important to compliment this with additional information. It's important to have a catchy tagline that intrigues the user enough that they will want to download the app.

Are you someone who likes to be challenged? Do you like to play word games that will keep your mind guessing and your brain ticking? Then download one of the most exciting FREE apps that you will ever play RIGHT NOW…. This is guaranteed to keep you entertained for hours with its engaging puzzles and phrases.

Website

Additional Information

Numbagories is a FREE Android application where the aim is for you to solve the puzzles, earn points and achievements, evolve through the ranks, and complete the game. The quicker you solve the puzzles, the more points you will earn. Try and earn all the achievements to gain extra points.

Are you someone who likes to be challenged? Do you like to play word games that will keep your mind guessing and your brain ticking? Then download one of the most exciting FREE apps that you will ever play RIGHT NOW…. This is guaranteed to keep you entertained for hours with its engaging puzzles and phrases.

Comprising of 101 brilliantly addictive levels, ranging in levels of difficulty, Numbagories is suitable for all ages and will have your mind boggled, your tongue twisted, and your head rattled as you race against the clock to achieve those precious points.

The aim is to solve a collection of the most commonly used phrases. But it's not going to be easy. You will only be presented with the number and the initial letter of each word. The quicker you solve the puzzles, the more points you will earn. The more puzzles you solve, the more achievements you will earn. Try and earn all the achievements to gain extra points.

So what are you waiting for? Name that Numbagory!

◆ INSTANT FUN ◆ No intricate rules or registration. Just download and play now.

◆ ENGAGING AND ENJOYABLE BRAIN TEASERS FOR ALL AGES ◆ Ranging in levels of difficulty, this puzzle game caters for all ages, all levels of knowledge, and a game that the entire family can play.

◆ ADDICTIVE AND EXCITING PUZZLES ◆ Discover the link between the number and the letters provided to solve the puzzle. Can’t find the answer? Use the hints or share the level to play along with friends.

Everyone who is anyone is playing this game! Don’t be the only one left out. Download it NOW for FREE to play along.

Promotional Video

F ind Out More

Already a fan of Numbagories, then like and follow us on our social media channels to support and stay up to date with the latest news:

Instagram: https://www.instagram.com/numbagories/
Facebook: https://www.facebook.com/numbagories
Twitter: https://twitter.com/numbagories
LinkedIn: https://www.linkedin.com/showcase/numbagories

References

Human Factors International, 2011. The ROI of User Experience. [online] Available at: https://www.youtube.com/watch?v=O94kYyzqvTc . (Accessed 25 September 2020)
The Futur Academy, 2020. How to Apply a Color Palette to Your Design - Tutorial. [online] Available at: https://www.youtube.com/watch?v=eXcKOqviLE0 . (Accessed 25 September 2020)
Usability.Gov, 2017. Benefits of User-Centered Design. [online] Available at: https://www.usability.gov/what-and-why/benefits-of-ucd.html . (Accessed 25 September 2020)

Key Notes from the Keynotes: IT@Cork TechFest Conference 2020

Fri, 18 Sep 2020 11:57:45 GMT

10 Minute Read

The following are my thoughts and overview from each of the keynote speakers during this years IT@Cork's TechFest Conference. All thoughts, views, and opinions are mine.

Conference Schedule

It was great to be involved with IT@Cork this year and organising the IT@Cork TechFest Conference. Due to the ongoing pandemic, it was decided to host the annual IT@Cork Tech Summit virtually. With something that was on the cards for years, this enabled IT@Cork to rebrand, create a new website, and also deliver this conference online creating the ability to reach a broader audience.

Figure 01: Graham Baitson, Gillian Bergin, and Eoghan O'Mahony at the Launch of the IT@Cork TechFest Conference 2020

This year was bigger, bolder, and better than ever, with it being a week-long technology festival comprising of 5 tracks with the addition of workshops. We even gave the audience the opportunity to vote for the tracks that they would wish to see, and we gave them what they asked for; Smart Cities, Cyber Security, Future of Education, Future of Work, and Digitalisation of BioPharma Manufacturing.

Figure 02 - IT@Cork TechFest Schedule

A big thank you to all the speakers. It's never an easy job collating all the information, making it interesting, and leaving the listener/viewer with some educational and though-provoking insights.

Figure 03 - TechFest Speakers

Track 1: Smart Cities/IoT (Keynote - Drone Deliveries)

Within the last few months, we have all been adapting to our unusual circumstances that have been besieged upon us. By social distancing and, in some cases, quarantining, we have had to look for alternate ways in which to interact with the world around us. Focusing on the silver lining, the advancements in digital and technology has enabled us to stay connected and also accelerate the non-technical savvy people and people at risk to utilise the range of technology available to live their life as normal as possible. Many people have become accustomed to getting their food and packages delivered to their door. But how would you feel about getting your items delivered by drones? Well this was the topic of discussion that kicked off this years IT@Cork's TechFest Conference.

Figure 04 - Manna Drone Delivery

Starting with a poll, 95% of the viewers of TechFest said they would be willing to accept their delivery by drone. This number would have been most likely a lot lower without the recent increase in home deliveries, but what would be your biggest concern if you were to think of a drone delivering your package? During the keynote, founder of Manna Drone Delivery, Bobby Healy, debunked a lot of the initial assumptions and concerns that people normally have when considering drone-as-a-service delivery, primarily around noise disturbance, privacy, and reliability. He stated that with a flying frequency of 50Hz, even at night, the drone is relatively quiet and therefore should not cause much disturbance. From a privacy concern, the drones have no recording equipment, does not store any customer data, doesn't even know what it's carrying, and is fully autonomous. When discussing reliability, he stated that the drones can fly in 99% of Irish weather; can fly in heavy rain and with a maximum wind speed of 40mph. Finally in relation hijacking, as there is no network connection on the drones themselves, there is no way to access them without physically interaction.

So with all of this information, how likely would you be to receive your packages via a drone? Are you convinced that this service is secure? Would you trust that your package will be reliably and securely delivered?

Track 2: Cyber Security (Keynote - A New Era of Threats and Complexity)

In one of my recent articles ' We Are At War... A Cyber War; With 20 Billion Connected Devices. Just How Safe Do You Feel? ', I gave an overview of the cyber-security threat landscape and how connected devices are resulting in us becoming digitalised versions of ourselves. And from what we've heard from Rik Ferguson of Trend Micro, these numbers have been continuing to grow since. During his talk, he mentioned that the cyber crime industry is now worth $1.5 trillion annually, with some companies that we've never even heard of, holding 11,000 data points on people across 62 different countries. But the threats are not only towards individuals, they are also towards commercial and national entities, with the offer of buying data, logs, phone numbers, access, propaganda, fake news items, etc... all on the black market.

Figure 05 - Organisations Architecture of the Future

These potential threats could then be amplified as we move into the future of organisations owning no architecture. Ferguson said that organisations will start to solely rely on as-a-service products, that can be spun up with all their dependencies and create mountains of data. This could create a wave of concerns due to the move towards volatile and software defined networks, machine to machine subscribers, vast amounts of data, the use of non data centric user patterns, and an exponentially greater surface for attack. Ferguson ended explaining that volume of threats that banks receive per day is upwards of 100,000, with each one taking a security operations centre (SOC) analyst spending 20-25 minutes per alert. This results in 41667 hours of effort per day which breaks down to over 5200 people to deal with these issues.

Looking at these figures above, how important a role do you see machine learning (ML) and artificial intelligence (AI) playing in the future of protecting people and organisation's data and valuables?

Track 3: Future of Education (Keynote - Technology and the Future of Education)

In one of my recent articles ' Are Humans the Next Horse? The Rise of the Robots ' I discussed the future of education and the importance of shifting from a predominantly left brain focused curriculum to a right brain. We have all seen the impacts that the latest events has had on education, specifically in relation to children not being able to go to school. Parents around the world have been forced to step into the professional educators footsteps, and in turn, realising just how difficult it actually is. Virtual reality (VR) is one technology which can help bridge this gap. VR has been used for years by the likes of NASA for training, but it's only within the last few years that it has become mainstream available due to the price becoming relatively affordable. David Whelan, CEO of VR Education, explained during his keynote, how VR can be introduced to education allowing not only this shift to a right brain focused curriculum, but also tackle many challenges and future progression when it comes to education.

Video 01 - ENGAGE, VR Education

Not only does VR allow for distance learning, it has also been proven that VR allows for a retention rate of 80% compared to that of 20% for traditional training methods (Training Industry, 2018). Whelan then went on to say that he sees the future of education being tailored by the individuals. For example, you will soon have the option to sit in a virtual classroom in MIT and take a physics lecture in the morning, and then sit in a virtual classroom in Cambridge and take a literature lecture in the afternoon. You will also have the option to choose educators that suit your style of learning. For example, if you learn better through visual interaction, you can pick an educator that has a more visual approach to teaching. From an educator point of view, Whelan sees this as an opportunity for educators to specialise further in specific areas.

As my first job was part of a team who developed a virtual reality, haptic based medical simulator for the training and assessment in ultrasound-guided regional anaesthesia, I've seen first hand how much of a positive impact these type of training and teaching methods can have. But there can also be challenges. For example, there are studies that show when spending too much time immersed within a VR environment, dizziness and disorientation, among others, can be caused, so it's advisable to take a 10-15 minute break every 30 minutes (Business Insider, 2018).

What do you think of VR education? Do you think the positives outweigh the negatives? Are you excited for this? Would you take a course that was delivered through VR?

Track 4: Future of Work (Keynote - The Future of Work and Things to Come)

It doesn't really matter what industry you are in, everyone has been impacted from a professional perspective in some shape or form during the last few months. Whether you are forced to work from home and not only miss the interactions with your colleagues, but also miss getting nuggets of information from passing each other in the corridors, whether you now have to wear a mask when interacting with people which in turn can lead some certain difficulties, or whether you have been in the unfortunate position that you have lost your job and now have to look for alternate ventures, everyone has had to and will be forced to adopt a new way of working..... but what will this be like long-term?

Figure 06 - Tom Raftery Discussing the Future of Work

The keynote from Tom Raftery, Global VP, Futurist, and Innovation Evangelist at SAP, started off with a poll that resulted in 59% of people saying that they would like to continue with a mix from working from home and working in the office. As a futurist, Raftery looks at trend lines of technology, the impact of these technologies, analyses, and then predicts what the future looks like for that particular technology. In relation to COVID, Raftery doesn't see much changing until a vaccine is put in place, which will most likely take up to 12 more months. During this time, we are going to see a rise in the cost of living. Tasks such as visiting the hairdressers now require advanced booking, wait for the area to be disinfected before and after use, etc... which all results in a higher cost for the consumer. If you look into other industries such as manufacturing, Raftery outlined that with physical distancing measures being put in place, this means that less work can get done on a manufacturing line. The options in this case are to spin up a new line (if there is space to do so), put on extra shifts (if that's possible), or increase automation. All of which have cost implications, but with the automation option, the result will be at least the same output with fewer staff.

"We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten" - Bill Gates

Being a futurist and trying to predict trends is even more challenging in these uncertain times. A lot of the predictions have been put on hold due to the current events. Jobs will be lost, lots of them. But Raftery concluded his keynote by outlining the mammoth tasks the world is undergoing should it need to roll-out an ongoing vaccine. People will need to be employed into areas such as contact tracing, distribution, etc... The logistics required will be enormous and on a scale never seen before. If a booster is required, that's up to 7.8 billion people per year will need access to this treatment, possibly even vaccination passports to prove that you are not contagious.

So taking everything into account, what new industries do you see advancing as a result of COVID? Do you see any long-term psychological affects as a result of social distancing, lack of interaction, inability to care for loved one, etc...?

Track 5: Digitalisation of BioPharma Manufacturing (Keynote - The Power of Data in Biopharma and Manufacturing 4.0)

At the start of the year, and even at the start of the pandemic, I think most of us would have never thought that in September 2020 we would still be locked down. It now seems as the only way out of this pandemic is when a vaccine has been developed and becomes mainstream available. But just how difficult is it to make a vaccine? In his keynote, Dr. Colin Clarke, Principal Investigator at The National Institute for Bioprocessing Research and Training (NIBRT), gave an overview of the process of creating pharmaceutical drugs and how data plays a big part in understanding the structures.

Figure 07 - A Typical mAb (antibodies that are made by identical immune cells) Manufacturing Process

When comparing antibodies and molecules to your regular over-the-counter drugs (e.g. Aspirin), the process of complication are orders to magnitude greater. Clarke explained that the biopharmaceutical manufacturing process is so complex, that the molecules consist of more atoms that stars in the universe. But data in constantly helping to improve this process, especially with the introduction of machine learning. By constantly analysing the data at each step along the creation process, monitoring the environment, measure the characteristics, taking corrective measures to fix any issues, machine learning can look into the future of the process and determine if the process will result in an incorrect molecule.

"If you torture your data long enough, it will confess" - Ronald Coase

Data lies at the heart of everything in Biopharma 4.0. Cenk Undey from Amgen recently gave an overview of the amount of data analyses during the manufacturing of their products. He stated that within research and development, one of the robotics-based drug screenings generated 200,000 data points per day and that 500 million continuous data points are generated per product from manufacturing equipment (Umetrics, 2019). Now although in big data terms, so of these wouldn't compete with other industries, Clarke went on to mention that the levels of complexity of biological systems are far beyond anything else. When working with these levels of data, Clarke concluded that collaborating with people from different backgrounds and also industry partners is essential, and outlined the following important factors in order to ensure performance and accuracy.

Scalability - eliminate complexity and disruption
Cost Efficiency - use commodity hardware
Flexibility - handle structured and unstructured data
Performance - avoid the overheads of traditional systems

Considering how complex and unstable our biological internal systems are, when do you think we should expect to see a vaccine?

Final Thoughts

The ongoing pandemic, along with natural disasters, climate change, and other international events, are leaving huge irreparable dents in our planet, our lives, and our minds. The world is constantly changing, and if history has thought us anything, it's that we must adapt in order to survive. I'd be interested in getting your thoughts on some of the questions I raise above. Until next time, I hope you enjoyed the read. Stay safe - GB.

References

Business Insider. 2018. Here's what happens to your body when you've been in virtual reality for too long. [online] Available at: https://www.businessinsider.com/virtual-reality-vr-side-effects-2018-3?r=US&IR=T . (Accessed 16 September 2020).
Figure 03: IT@Cork TechFest Schedule. [online] Available at: https://www.itcork.ie/wp-content/uploads/2020/07/it@cork-Schedule-Overview-Final-1-1.png
Figure 04: Manna Drone Delivery. [online] Available at: https://www.irishtimes.com/business/technology/ucd-campus-first-stop-for-drone-takeaway-food-delivery-1.4184857
Training Industry. (2018). 3 Ways Virtual Reality Training Is Producing Better Outcomes. [online] Available at: https://trainingindustry.com/articles/learning-technologies/3-ways-virtual-reality-training-is-producing-better-outcomes/ . (Accessed 16 September 2020).
Umetrics. (2019). How Digital Transformation Helped Amgen Implement Real-Time Process Control. [online] Available at: https://blog.umetrics.com/how-digital-transformation-helped-amgen-implement-real-time-process-control . (Accessed 18 September 2020).
Video 01: ENGAGE, VR Education. [online] Available at: https://www.youtube.com/watch?time_continue=26&v=m_44MehaXxU

The Rise of Ethics in Artificial Intelligence (Part 3: Trustworthy AI)

Mon, 17 Feb 2020 19:09:03 GMT

8 minute read

In my previous article ‘ The Rise of Ethics in Artificial Intelligence (Part 2: Content Ownership) ’, I highlighted some interesting stories that blur the lines between technology and humanity. In this final article of the series, I will outline what some of the industry leaders are doing in order to ensure trustworthy AI, and also some interesting areas to keep an eye on. All thoughts, views and comments are my own.

The Ruler of the World

In 2018, at a Special Town Hall Event with Google and YouTube (Eventbrite, 2018), Google CEO Sundar Pichai said that “AI will have a bigger impact on the world that some of the most ubiquitous innovations in history” and that it is “more profound than electricity or fire” (Cranz, 2018). The uncertainty around the exact ‘impact’ and ‘profoundness’ of which is under constant debate amongst industry leaders and public figures. Some of the predictions of AI taking over the world, creating a new wave of cyberattacks, superhuman hacking, and even autonomous weapon systems, sound like a dystopian nightmare taken straight from an episode of Black Mirror. In September 2017, Russian President Vladimir Putin said that AI will create “colossal opportunities, but also threats that are difficult to predict” and also whoever becomes the leader in artificial intelligence “will become the ruler of the world” (James, 2017). Elon Musk replied on Twitter to these comments by stating that the “competition for AI superiority at national level will most likely be the cause of WW3” (Lant, 2017). And even the great theoretical physicist Stephen Hawking has advised creators of AI to “employ best practice and effective management” as the “success in creating effective AI, could be the biggest event in the history of our civilization. Or the worst. We just don’t know” (Kharpal, 2017). ‘We just don’t know’ sums up the uncertainty that surrounds the collective thoughts as we move towards the inevitable progression of AI, but now let us look at some of the safe guards that are being put in place to try and ensure that AI is created for good and not evil.

Figure 1: AI Army

The Ethics of Trustworthy AI

The rapid rise of AI and machine learning has led to growing calls to examine its impact on society, with experts warning of the technology's potential misuse if it isn't controlled.

Strategy

One of the ways in which this is being examined is by the High-Level Expert Group on AI (HLEG-AI). This independent expert group was created by the European Commission in 2018 to define a European strategy on AI and focus on defining human centred policies around ethical, legal, and societal issues. Towards the end of 2018, this group released the first draft of its ‘Ethics Guidelines for Trustworthy Artificial Intelligence’, which was then published in April 2019 (European Commission, 2019a). Part of these outlined the following seven essentials for achieving trustworthy AI.

Figure 2: Ethics Guidelines for Trustworthy AI

Complimenting this document, the group followed up in June 2019 by publishing the ‘Policy and Investment Recommendations for Trustworthy Artificial Intelligence’ (European Commission, 2019b). Professor Barry O’Sullivan, who is the Vice Chair of the HLEG-AI, President of the European Artificial Intelligence Association (EurAI), and also founding Director of the Insight Centre for Data Analytics at UCC, is holding a Trustworthy AI Event this coming Wednesday 19th February at the Aviva Stadium, Dublin (Eventbrite, 2020), aimed at discussing these recent developments and guidelines related to trustworthy AI and also the emerging regulations to come, more of which can be read in the recent Silicon Republic article, ‘Trustworthy artificial intelligence – is new EU regulation coming for AI?’ (Silicon Republic, 2020).

Research

In addition to expert groups looking into these ethical guidelines, a number of advancements in research has also been underway. In 2018, the 82nd richest person in world Stephen Schwarzman, donated $350 million to Massachusetts Institute of Technology to set up the MIT Schwarzman College of Computing to focus on the opportunities, challenges, and ethical and policy implications by the rise of AI. In June 2019, he then donated $188 million to the University of Oxford, their largest single donation in hundreds of years, to help fund the research into studying the ethical implications of AI. Schwarzman stated, “What motivates me, among other things, is to have the core of humanities, the basic values of people, be considered in the context of technological development. Technology left unaffected would trample over certain aspects of human behaviour and human opportunities” (Carpani, 2019). Tim Berners-Lee, the inventor of the world wide web, voiced his support for Schwarzman's donation to Oxford: "It is essential that philosophy and ethics engages with those disciplines developing and using AI" he said in a statement shared by the university. "If AI is to benefit humanity we must understand its moral and ethical implications" he added (Rishi, 2019).

Future Trends

The following are just some interesting areas that I feel will be worth keeping an eye on as we move towards ensuring AI ethics is at the forefront of the creation of AI applications. I may write an article going into more future trends and further expanding the areas below.

Biometrics

We are all becoming more familiar with biometrics due to the advancement of technology in our mobile devices. It is estimated that the value of the global biometric market will grow from $33 billion to $65.3 billion by 2024 (Markets and Markets, 2018). Both government and business are starting to adopt this technology at an alarming rate. But is this progress or an invasion of our privacy and erosion of our freedom?

Identification: In 2016, Saudi Arabia enforced new regulations that required all telecommunication subscribers to register their fingerprints (Arab News, 2016). Also in 2016, both Hungary and Turkey started distributing biometric identity cards that contains a chip that can store peoples fingerprints, electronic signature, social security, and tax information (Mayhew, 2016a)(Mayhew, 2016b). In 2017, Pakistan introduced biometric passports to reduce the risk of forgery and also human trafficking by authenticating the identity of each traveller (Tribune, 2016). In 2018, India decided to continue with the world’s largest biometric identification program with almost the entire population of India’s (1 billion people) name, gender, date of birth, fingerprints, iris scans, and photos linked to a 12 digit number and registration card that they can use for a range of government services, banking and telephony (Ayyar, 2018).

Authentication: In 2017, Dubai airport announced that they will now use a virtual aquarium styled tunnel, fitted with 80 cameras, to scan passengers faces as they walk through security clearance (Ong, 2017). Last year, Barclays in collaboration with Hitachi, developed a finger vein scanner that uses infra-red technology to identify specific vein patterns in an attempt to further secure transactions (Barclays, 2019).

Robotic Responsibility

In one of my previous articles ‘ Are Humans the Next Horse? The Rise of the Robots ’, I discussed the impact of automation on the workforce. But what could this mean from a society point of view?

Robot Tax: It’s clear that no one knows for certain the exact impact that AI will have on the workforce; but inevitably, certain tasks will be automated. But how will the displaced workforce find meaning if their careers have come to a premature conclusion? And also what will happen if companies simply no longer need human workers? One idea that Bill Gates has suggested is that robots should be taxed. Not only would this give society time to adjust to the adoption of this technology, but it could also pay for further education opportunities and employment in soft-skilled careers. Now this needs a lot of consideration, with some of the advantages and disadvantages of the approach outlined quite nicely in the Emerj article ‘Robot Tax – A Summary of Arguments For and Against’ (Walker, 2019).

Citizenship: In 2017, Sophia the Robot from Hanson Robotics was famously given citizenship of Saudi Arabia (Stone, 2017). This is a really interesting concept that has caused a lot of controversy. Regardless of how woke Sophia has been programmed to be, does she deserve the acknowledgement to the full set of citizen rights?

Final Thoughts

It almost feels like every day there is a new advancement in technology. Companies are fighting to be the first to conquer in the discovery of AI dominancy. Some of the areas above outline how we are best trying to put guide-rails in place to ensure that this technology is used to compliment and augment the way we live in a positive manner.

With Sophia, is the prioritisation of technological utopia over the rights and lives of humans the right thing to do? Does this give the permission towards the removal of human responsibility should something go wrong? There’s a lot of questions to answer here to understand which direction we are heading. We are constantly pushing the boundaries between technology and human interaction, a boundary that is becoming thinner and thinner. But is it possible to control the genie once it is out of the bottle? Should we hold onto our 3 wishes just in case?

Until next time, I hope you enjoyed the read. GB

References

Arab News. (2016). Fingerprint to be recorded for issuance of mobile SIM. [online] Available at: https://www.arabnews.com/saudi-arabia/news/870691 . (Accessed 12 February 2020).
Ayyar, Kamakshi. (2018). The World's Largest Biometric Identification System Survived a Supreme Court Challenge in India. [online] Available at: https://time.com/5388257/india-aadhaar-biometric-identification/ . (Accessed 12 February 2020).
Barclays. (2019). Barclays and Hitachi launch next-generation finger vein scanner. [online] Available at: https://home.barclays/news/press-releases/2019/11/barclays-and-hitachi-launch-next-generation-finger-vein-scanner/ . (Accessed 17 Februrary 2020).
Carpani, Jessica. (2019). Oxford University given £150m by US billionaire to investigate AI in biggest ever donation. [online] Available at: https://www.telegraph.co.uk/news/2019/06/19/oxford-university-given-150m-us-billionaire-found-ai-institute/ . (Accessed 12 February 2020).
Cranz, Alex. (2018). Google CEO Says AI Is 'More Profound Than, I Dunno, Electricity or Fire'. [online] Available at: https://gizmodo.com/google-ceo-says-ai-is-more-profound-than-i-dunno-elec-1822635900 . (Accessed 5 February 2020).
European Commission. (2019a). Ethics Guidelines for Trustworthy AI. [online] Available at: https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines . (Accessed 5 February 2020).
European Commission. (2019b). Policy and investment recommendations for trustworthy Artificial Intelligence. [online] Available at: https://ec.europa.eu/digital-single-market/en/news/policy-and-investment-recommendations-trustworthy-artificial-intelligence . (Accessed 12 February 2020).
Eventbrite. (2018). A Special Town Hall Event with Google and YouTube. [online] Available at: https://www.eventbrite.com/e/a-special-town-hall-event-with-google-and-youtube-tickets-41722062813# . (Accessed 5 February 2020).
Eventbrite. (2020). Trustworthy AI Event, Aviva Stadium. [online] Available at: https://www.eventbrite.ie/e/trustworthy-ai-event-aviva-stadium-entrance-a-tickets-89767461895?aff=ebdssbeac . (Accessed 12 February 2020).
Figure 0: Cover. [online] Available at: https://miro.medium.com/max/7680/1*Vx3iseHaMpM6156T8vx3Dg.jpeg
Figure 1: AI Army. [online] Available at: https://i.pinimg.com/originals/8c/90/9d/8c909dc7ee5327ad5a18912f8c1e2865.jpg
Figure 2: Ethics Guidelines.
Gorey, Colm. (2019). EU reveals its 7 essentials for achieving trustworthy AI. [online] Available at: https://www.siliconrepublic.com/machines/ai-ethics-eu-guidelines-2019 . (Accessed 5 February 2020).
Iyengar, Rishi. (2019). Stephen Schwarzman gives $188 million to Oxford to research AI ethics. [online] Available at: https://edition.cnn.com/2019/06/19/tech/stephen-schwarzman-oxford-ai-donation/index.html . (Accessed 13 February 2020).
Kharpal, Arjun. (2017). Stephen Hawking says A.I. could be ‘worst event in the history of our civilization’. [online] Available at: https://www.cnbc.com/2017/11/06/stephen-hawking-ai-could-be-worst-event-in-civilization.html . (Accessed 5 February 2020).
Lant, Karla. (2017). Elon Musk: Competition for AI Superiority at National Level Will Be the “Most Likely Cause of WW3”. [online] Available at: https://futurism.com/elon-musk-competition-for-ai-superiority-at-national-level-will-be-the-most-likely-cause-of-ww3 . (Accessed 5 February 2020).
Markets and Markets. (2018). Biometric System Market by Authentication Type (Single-Factor: Fingerprint, Iris, Palm Print, Face, Voice; Multi-Factor), Offering (Hardware, Software), Functionality (Contact, Noncontact, Combined), End User, and Region - Global Forecast to 2024. [online] Available at: https://www.marketsandmarkets.com/Market-Reports/next-generation-biometric-technologies-market-697.html?gclid=CjwKCAiA4Y7yBRB8EiwADV1haSyazciY7-Q_PNNWkAjSlJT1WZQ2-W3CrfYrHm_lyLFRqnPej9WpiBoCp30QAvD_BwE . (Accessed 12 February 2020).
Mayhew, Stephen. (2016a). Hungary begins issuing biometric id cards. [online] Available at: https://www.biometricupdate.com/201601/hungary-begins-issuing-biometric-id-cards . (Accessed 12 February 2020).
Mayhew, Stephen. (2016b). Turkey starts distributing biometric identity cards. [online] Available at: https://www.biometricupdate.com/201603/turkey-starts-distributing-biometric-identity-cards . (Accessed 12 February 2020).
Ong, Thuy. (2017). Dubai Airport is going to use face-scanning virtual aquariums as security checkpoints. [online] Available at: https://www.theverge.com/2017/10/10/16451842/dubai-airport-face-recognition-virtual-aquarium . (Accessed 17 February 2020).
Silicon Republic. (2020). Trustworthy artificial intelligence – is new EU regulation coming for AI? [online] Available at: https://www.siliconrepublic.com/machines/trustworthy-ai-eu-regulation . (Accessed 16 February 2020).
Stone, Zara. (2017). Everything You Need To Know About Sophia, The World's First Robot Citizen. [online] Available at: https://www.forbes.com/sites/zarastone/2017/11/07/everything-you-need-to-know-about-sophia-the-worlds-first-robot-citizen/#1112e71446fa . (Accessed 17 February 2020).
Tribune. (2016). Biometric passports to be introduced in 2017. [online] Available at: https://tribune.com.pk/story/1103021/biometric-passports-to-be-introduced-in-2017/ . (Accessed 12 February 2020).
Vincent, James. (2017). Putin says the nation that leads in AI ‘will be the ruler of the world’. [online] Available at: https://www.theverge.com/2017/9/4/16251226/russia-ai-putin-rule-the-world . (Accessed 5 February 2020).
Walker, Jon. (2019). Robot Tax – A Summary of Arguments “For” and “Against”. [online] Available at: https://emerj.com/ai-sector-overviews/robot-tax-summary-arguments/ . (Accessed 17 February 2020).

The Rise of Ethics in Artificial Intelligence (Part 2: Content Ownership)

Tue, 21 Jan 2020 18:51:12 GMT

8 minute read

In my previous article ' The Rise of Ethics in Artificial Intelligence (Part 1: Privacy) ', I outlined some privacy concerns that the enjoyment and convenience of our connected devices are leading to the intrusiveness of our behaviours and patterns. In this article, I will highlight some interesting stories that blur the lines between technology and humanity. All thoughts, views and comments are my own.

Technology vs. Humanity

We are constantly threading the boundaries between technology and humanity, but how did we end up here? Well we now have access to mass amounts of data. It was estimated that there was more data created in 2019 than in the entire history of the internet (Gorey, 2015). Computing power has advanced to the point now of using supercomputers that can process 200,000 trillion calculations per second (BBC News, 2018). Combining the two previous points provides a powerful platform to run the algorithms that have been developed by some of the brightest minds. The following are some examples that highlight not just the technological issues, but also human ones when it comes to technology intersecting our lives.

The Monkey Selfie

In 2011, a photographer called David Slater was traveling through Indonesia photographing a troop of macaques. On trying to get the perfect shot, he decided to set up a camera on a tripod. When he returned, he found the troop ‘monkeying’ around with his equipment – “They were quite mischievous, jumping all over my equipment. One hit the button. The sound got his attention and he kept pressing it. At first it scared the rest of them away but they soon came back – it was amazing to watch” (Morris, 2011). This resulted in probably the most amazing selfie you are likely to see.

Figure 1: Monkey Selfie

But this selfie has been the subject of a number of debates around ownership and copyright. After Slater published the image in a book, the image went viral, which lead to a complicated legal dispute in 2014 when Slater asked Wikipedia to stop using the monkey selfie image without his permission. Wikipedia refused claiming that the photograph cannot have copyrights because the monkey was the actual creator of the image (Wong, 2017). In addition to this, in 2015, the People for the Ethical Treatment of Animals (Peta) pushed to have the monkey “declared the author and owner of the photograph” by filing a law suit against Slater on behalf of the macaque (The Guardian, 2017). This is an interesting case, and sets the scene of how this relates to AI.

The AI Artist

In one of my previous articles, ‘ Microsoft Paint – For the AI Generation ’, I talked about how we can turn our doodles into masterpieces. But how about creating masterpieces without the need for a doodle? Well in October 2018, a piece of artwork that sold during an auction in Christies, made the news for a very unique reason; it was the first time that an auction house had presented a work of art created by an algorithm. It was estimated to sell for approximately $10,000 but actually sold for just over $430,000 (Christie’s, 2018).

Figure 2: AI Generated Artwork - Edmond De Belamy

It all started when 19-year old Robbie Barrat, who is now currently working at a Stanford University AI Research Lab, released open-source code that utilised a generative adversarial network (GAN) to understand the relationships between different features, and as a result, would produce new material based on the data that was fed into the algorithm, some of which can be seen below from almost a year previous to the artwork that was sold at auction. In the spirit of the open-source community, Barrat’s intention was to “help and inspire” others, but when a Parisian art collective by the name of ‘Obvious’ took his code in order to make a profit, this sparked a debate around ownership and ethics. So in essence, Obvious utilised Barrat’s code, made some minor changes, fed over 150,000 pieces of art to the algorithm, and created the peace of artwork which ultimately sold for over $430,000 (Vincent, 2018).

Figure 3: Robbie Barrat Neural Network Output

This raises the question of who owns this piece of artwork? Who is the artist – is it Barrat who developed the original codebase, because without his code there would be no artwork, or is it the group Obvious, because without them amending the code and feeding the images into the algorithm there would also be no artwork? But if you compare this to how humans learn, we mimic those around us, we learn from our teachers, we put together the pieces that we like and build upon them, and we discard the rest. It’s how we create music, how we create art, how we create technology. So for this comparison, one could argue that in this case Barrat is the teacher, and the AI is the student.

AI Harmony

Using the same approach that created the artwork above, GANs can also be applied to produce digital content. In March 2019, to celebrate Johann Sebastian Bach’s birthday, Google provided a Doodle that allowed you to create a melody using piano keys on the screen. It then converted this into a musical piece in the style of Bach using a GAN that analysed more than 300 Bach compositions (Vincent, 2019).

In 2017, a British band called Shaking Chains’ took part in an algorithmic filmmaking experiment for their debut single ‘Midnight Oil’. They used a bespoke algorithm that used specific search terms in order to retrieve online video content that resulted in a different video each time the music video was played (Holmes, 2017). This video doesn’t seem to be working now, but I remember looking at it when it first came out. Similarly in 2017, the British band Muse released a music video for their song ‘Dig Down’ that changes every 24 hours. They used algorithms that scrape online video content and stitch together clips that match the lyrics of the song (Haridy, 2017). But not only can it create music and video content, it can also produce lyrics. Barrat, the same guy from the AI art above, created an algorithm to use 6,000 Kanye West lyrics and rearrange into new sequences and generate a complete song based on a similar feel (Glenn, 2017).

Final Thoughts

With the advancements in technology, if we are not careful, we will soon lose control of what’s being developed. Our machines are becoming ‘smarter’ and producing outputs that we will no longer understand. We have seen examples of utilising GANs to generate artwork and digital content. Even since the AI artist, a humanoid robot has made us question the nature of creativity by creating art that has sold for more than £1 Million (Interesting Engineering, 2019). The boundaries of art and technology are continuing to be explored by aiming to create a 3D printed painting by using all of Rembrandt’s paintings (Dutch Digital Design, 2018). At what point are we going to see complete AI generated music, novels, and screenplays hitting our charts, and how will this change concerts and red carpet events in the future? In my next article, I will talk about what is being done to ensure that this AI generated content and future applications are done in a trustworthy manner.

Until next time, I hope you enjoyed the read. GB

References

BBC News. (2018). US debuts world's fastest supercomputer. [online] Available at: https://www.bbc.com/news/technology-44439515 . (Accessed 15 January 2020).
Christie’s. (2018). Is artificial intelligence set to become art’s next medium? [online] Available at: https://www.christies.com/features/A-collaboration-between-two-artists-one-human-one-a-machine-9332-1.aspx . (Accessed 15 January 2020).
Dutch Digital Design. (2018). The Next Rembrandt: bringing the Old Master back to life. [online] Available at: https://medium.com/@DutchDigital/the-next-rembrandt-bringing-the-old-master-back-to-life-35dfb1653597 . (Accessed 15 January 2020).
Figure 0: Cover. [online] Available at: https://www.worldaishow.com/articles/wp-content/uploads/2018/02/world-ai-show-sm-article-3-1.jpg . (Accessed 15 January 2020).
Figure 1: Monkey Selfie. [online] Available at: https://en.wikipedia.org/wiki/File:Macaca_nigra_self-portrait_large.jpg . (Accessed 15 January 2020).
Figure 2: AI Generated Artwork - Edmond De Belamy. [online] Available at: https://www.christies.com/media-library/images/features/articles/2018/08/09/a-collaboration-between-two-artists-one-human-one-a-machine/edmond-de-belamy-framed-cropped.jpg . (Accessed 15 January 2020).
Figure 3: Robbie Barrat Neural Network Outputs. [online] Available at: https://twitter.com/DrBeef_/status/1055285640420483073/photo/2 . (Accessed 15 January 2020).
Glenn, E. (2017). Listen To An AI Rap Based On Kanye West’s Lyrics. [online] Available at: https://www.thefader.com/2017/03/17/ai-rap-kanye-west-lyrics . (Accessed 18 Janyary 2020).
Gorey, C. (2015). More data to be created in 2019 than in history of the internet. [online] Available at: https://www.siliconrepublic.com/comms/more-data-to-be-created-in-2019-than-history-of-the-internet . (Accessed 15 January 2020).
Haridy, R. (2017). The AI-generated music video that changes every 24 hours. [online] Available at: https://newatlas.com/ai-music-video-muse/50380/ . (Accessed 15 January 2020).
Holmes, K. (2017). [Premiere] Algorithmic Filmmaking Experiment Creates a New Music Video Every Time You Play It. [online] Available at: https://www.vice.com/en_us/article/9amjy5/shaking-chains-algorithmic-filmmaking-youtube-music-video . (Accessed 15 January 2020).
iHeart. (2018). The Complicated Story of an AI Artist. [online] Available at: https://www.iheart.com/podcast/105-techstuff-26941194/episode/the-complicated-story-of-an-ai-30087808/ . (Accessed January 3 2020).
IIEA. (2018). TOWARDS A EUROPEAN STRATEGY FOR ARTIFICIAL INTELLIGENCE. [online] Available at: https://www.iiea.com/economics/towards-a-european-strategy-for-artificial-intelligence/ . (Accessed 15 January 2020).
Interesting Engineering. (2019). An AI Robot Artist Is Creating Art That Has Sold for More Than £1 Million. [online] Available at: https://interestingengineering.com/an-ai-robot-artist-is-creating-art-that-has-sold-for-more-than-1-million . (Accessed 15 January 2020).
Morris, S. (2011). Shutter-happy monkey turns photographer. [online] Available at: https://www.theguardian.com/world/2011/jul/04/shutter-happy-monkey-photographer . (Accessed 15 January 2020).
The Guardian. (2017). British photographer wins court battle over monkey selfie. [online] Available at: https://www.thejournal.ie/monkey-selfie-3594714-Sep2017/ . (Accessed 15 January 2020).
Vincent, J. (2018). HOW THREE FRENCH STUDENTS USED BORROWED CODE TO PUT THE FIRST AI PORTRAIT IN CHRISTIE’S. [online] Available at: https://www.theverge.com/2018/10/23/18013190/ai-art-portrait-auction-christies-belamy-obvious-robbie-barrat-gans . (Accessed 15 January 2020).
Vincent, J. (2019). Google’s next Doodle uses AI to generate music in the style of Johann Sebastian Bach. [online] Available at: https://www.theverge.com/2019/3/20/18274077/google-doodle-johann-sebastian-bach-birthday-ai-machine-learning . (Accessed 15 January 2020).
Wong, J. C. (2017). Monkey selfie photographer says he's broke: 'I'm thinking of dog walking'. [online] Available at: https://www.theguardian.com/environment/2017/jul/12/monkey-selfie-macaque-copyright-court-david-slater . (Accessed 15 January 2020).

The Rise of Ethics in Artificial Intelligence (Part 1: Privacy)

Thu, 16 Jan 2020 18:32:28 GMT

8 minute read

As artificial intelligence (AI) is starting to consume our lives, ethics has never been more important than it is today. We are moving towards an era, where for the first time, experts are contradicting each other towards the uncertainty of our future. Considerations around ethics need to be at the forefront of the brightest minds who will be developing the algorithms and machines of the future. In the next three articles, I will take a snapshot look at the rise of ethics – starting with privacy and then followed by content ownership, the implications of AI, what is being done to ensure trustworthy AI, and some interesting areas to keep up to date with. All thoughts, views and comments are my own.

The Truman Effect

The very first breath of today’s generation is almost acceptance of the terms that our face will be immediately photographed and presented to the social realms for those all exclusive ‘likes’. We’re pretty much born without a decision, but does it get any better? As we roam the streets, do our shopping, drive our cars, or pop into our neighbours for a cup of coffee, our faces are becoming increasingly captured and recognised by surveillance cameras. How many times would you think, on average, you are caught on surveillance cameras per day? Well in the United States, it is estimated that the average citizen is caught up to 75 times per day on surveillances cameras, whereas in London, it is estimated that the average person is caught up to 300 times per day (Reolink, 2018). One can argue that these cameras are evading our privacy whereas others will argue that these are keeping us safe – either way, we need to look for ways that maintain our privacy whilst also keeping us safe.

Figure 1: The Truman Show

I'm a Good Citizen

In one of my previous articles “ We Are At War... A Cyber War; With 20 Billion Connected Devices. Just How Safe Do You Feel? ”, I discussed how, in China’s move towards a cashless economy, they had reached almost $13 trillion in mobile transactions in 2017, which has increased recently to $41.51 trillion in 2018 (China Daily, 2019). More and more of our life’s are becoming digitalised, so much so, that China have recently starting scoring a citizens ‘social credit’ based on whether they have committed any minor offenses. In 2018, this ‘trustworthy’ scoring (Independent, 2016) stopped 17.5 million people from buying airplane tickets, 5.5 million from hopping on a train, 290,000 people from getting a high-paying senior management job, and 128 from leaving the country because they had not yet paid their taxes (Fortune, 2019). The concept of this is extremely interesting, but do you think it is a good idea? Will the result of this force/encourage people to be better citizens or is it placing too much power in the government’s hands? What sort of catastrophes could be caused if there was a data breach – could a person be essentially removed from ever existing?

Figure 2: China’s Social Credit System

How Did You Know I Would Like That?

Is this familiar… you are browsing online for a product, and the next day you are on a completely different website and all of a sudden you notice an advert that is displaying a similar product that you were looking at previously? Is this just a lucky coincidence, or is it that your browsing profile and data been shared across different sites? The sharing of our personal data is being used to drive extremely personalised campaigns and customised services, but where do we draw the line between the best digital experience vs. violating our privacy?

Now take this digital experience to your physical stores. EyeSee mannequins, that use embedded cameras to determine your gender, race, age, and facial expressions in order to understand whether you like what you are looking at, are now being deployed in stores (Techno Fashion World, 2013). This information combined with location information from your mobile device could potentially be used to establish whether you made a purchase. This powerful information can be used to determine how to rearrange a shop, what clothes to put together, and also what highly personalised marketing to send afterwards. So the next time you look a mannequin and think, “Oh I like those clothes”, have a little think and wonder is the mannequin thinking the same about you. She may not be as lively as Kim Cattrall, but she could be watching you.

Figure 3: Eye See Mannequin

Terms and Conditions May Apply

How many of us actually take time to read the terms and conditions before we accept them? A recent survey by Deloitte found that 91% of people consent to legal terms and conditions without reading them, which increases to 97% of people when considering the ages between 18-34 (Business Insider, 2017). There’s a good example of this from PC Pitstop, who hid a $1000 prize in their terms and conditions and all the reader had to do was email them. It wasn’t until 5 months and 3,000 sales later that a user actually noticed it, emailed the team, and claimed the prize (TheUIJunkie, 2012).

Companies such as Facebook and Google have been criticised for having long-winded, misguiding, and unfriendly language within their terms and conditions. A recent study found that terms and conditions belong to some of the most commonly used websites and applications are almost unreadable to 99% of people, with some being compared to academic journals requiring over 14 years of education to understand (Vice 2019). This is proof that tech companies are making it harder and harder to use their services without giving up your personal information and data.

In the documentary ‘Terms and Conditions May Apply’, it was said that Google is essentially a $500 a year service, because that’s the value that is placed on the data that you provide. More and more companies are now gathering these types of data points and learning about our interests, fears, secrets, family, and friends… and we pretty much agree to the majority of it (IMDb, 2013). One of the biggest potential issues is that this data could be used as an input to an automated flagging system based on your search and online behaviours, a similar concept to that of the film Minority Report, and there has been some examples of this in the past. In 2012, two young tourists were refused entry to the United States on the security grounds that he previously tweeted saying he was going to “destroy America” – by which he meant ‘get drunk’... millennials huh (BBC News, 2012). In 2009, New York comedian Joe Lipari, ended up with two felony charges and spent a year proving he was not a terrorist after he was unhappy with the assistance he was given at an Apple store and paraphrased a quote from the film Fight Club on Facebook (Engadget, 2011).

Figure 4: Terms and Conditions May Apply

Final Thoughts

In 2011, Marc Andreessen stated that software is eating the world and in order to survive, every company must be a software company (A16z, 2011). It is almost inevitable that the convenience and enjoyment that our connection to the plethora of connected devices and application bring us, lead to the intrusiveness to our behaviours and patterns. Although the sharing of these types of information does come with advantages such as the accuracy and efficiency of Google Maps (which is said to have 20 million user contributions of information every day – that’s more than 200 contributions every second [Geospatial World, 2019]), is the tailoring of services based on your purchasing patterns and behaviours really that bad? Or is it the randomness that enriches our lives? In the casual flow of life, if we never get a chance to partake in the art of browsing and are denied the opportunity to stumble upon something new, has our freedom been taken from us… our freedom of choice? We are now at a stage where almost every company is a data company. Data has become king and it looks like we must learn to live in the kingdom. In my next article ' The Rise of Ethics in Artificial Intelligence (Part 2: Content Ownership) ', I will talk about some areas in which AI is generating content, and the implications that this has in terms of ownership.

Until next time, I hope you enjoyed the read. GB

References

BBC News. (2012). Caution on Twitter urged as tourists barred from US. [online] Available at: https://www.bbc.com/news/technology-16810312 . (Accessed 29 November 2019).
Business Insider. (2017). You're not alone, no one reads terms of service agreements. [online] Available at: https://www.businessinsider.com/deloitte-study-91-percent-agree-terms-of-service-without-reading-2017-11 . (Accessed 24 November 2019).
China Daily. (2019). Mobile payments continue meteoric rise. [online] Available at: https://www.chinadaily.com.cn/a/201903/21/WS5c932294a3104842260b1cc9.html . (Accessed 09 November 2019).
Engadget. (2011). First rule of Facebook: Don't quote Fight Club. [online] Available at: https://www.engadget.com/2011/06/28/first-rule-of-facebook-dont-quote-fight-club/ . (Accessed 11 January 2020).
Figure 0: Cover. [online] Available at: https://unsplash.com/photos/IhcSHrZXFs4 .
Figure 1: The Truman Show. [online] Available at: https://www.dazeddigital.com/film-tv/article/40216/1/the-original-truman-show-screenplay-was-way-way-darker . (Accessed 09 November 2019).
Figure 2: China’s Social Credit System. [online] Available at: https://www.visualcapitalist.com/the-game-of-life-visualizing-chinas-social-credit-system/ . (Accessed 09 November 2019).
Figure 3: Eye See Mannequin. [online] Available at: http://www.technofashionworld.com/eye-see-mannequin-the-smart-and-well-behaved-mannequin/ . (Accessed 09 November 2019).
Figure 4: Terms and Conditions May Apply. [online] Available at: https://images-na.ssl-images-amazon.com/images/I/81pcQLUXs6L._RI_.jpg . (Accessed 11 January 2020).
Fortune. (2019). China Banned 23 Million People From Traveling Last Year for Poor ‘Social Credit’ Scores. [online] Available at: https://fortune.com/2019/02/22/china-social-credit-travel-ban/ . (Accessed 09 November 2019).
Geospatial World. (2019). Most asked questions about the way Google Maps uses data. [online] Available at: https://www.geospatialworld.net/blogs/most-asked-questions-about-the-way-google-maps-uses-data/ . (Accessed 12 January 2020).
IMDb. (2013). Terms and Conditions May Apply. [online] Available at: https://www.imdb.com/title/tt2084953/ . (Accessed 24 November 2019).
Independent. (2016). China wants to give all of its citizens a score – and their rating could affect every area of their lives. [online] Available at: https://www.independent.co.uk/news/world/asia/china-surveillance-big-data-score-censorship-a7375221.html . (Accessed 09 November 2019).
Reolink. (2018). How Many Times Are You Caught on Security Camera per Day. [online] Available at: https://reolink.com/how-many-times-you-caught-on-camera-per-day/ . (Accessed 09 November 2019).
Techno Fashion World. (2013). Eye See Mannequin, the Smart and well-behaved mannequin. [online] Available at: http://www.technofashionworld.com/eye-see-mannequin-the-smart-and-well-behaved-mannequin/ . (Accessed 09 November 2019).
TheUIJunkie. (2012). The Company That Gave $1,000 To Anyone Who Had Read Their Terms Of Service. [online] Available at: https://theuijunkie.com/pc-pitstop-prize/ . (Accessed 11 January 2020).
Vice. (2019). Most Online ‘Terms of Service’ Are Incomprehensible to Adults, Study Finds. [online] Available at: https://www.vice.com/en_us/article/xwbg7j/online-contract-terms-of-service-are-incomprehensible-to-adults-study-finds . (Accessed 24 November 2019).

McKesson - 2018 Winners of the AI Awards "Best Application of AI in a Large Enterprise" Category

Fri, 16 Aug 2019 12:20:52 GMT

On the lead up to this year's 2019 AI Awards, here is my round-up from the 2018 AI Awards and information on why McKesson are being called ‘pioneers’ for their work with cutting edge technology. All thoughts, views and comments are my own.

Two Months, Two Awards

On 19th October 2018, McKesson Cork won "Multinational of the Year Award" at the IT@Cork Leaders Awards 2018. Rory Lankford, General Manager at McKesson Ireland, gave a great overview on how McKesson Cork have evolved since 2001 from a nine-employee software distribution company to McKesson's first Enterprise Technology Hub outside of the United States. Just on month later, on the 22nd November, McKesson continued their success by winning the "Best Application of AI in a Large Enterprise" at the 2018 AI Awards.

Figure 1: McKesson, Two Awards, Two Months

AI Awards

The AI Awards was setup by the non-profit organisation AI Ireland. The aim of these awards is to increase the public awareness of artificial intelligence (AI) by bringing academia and industry together to showcase and recognise the hard work and dedication in the field of AI within Ireland (AI Awards, 2018a).

The AI Awards were split into different categories representing start-ups, academia, research and industry. McKesson Labs, a newly formed software innovation team within McKesson Technology which focuses on innovation, design, developer services and automation products, applied to the "Best Application of AI in a Large Enterprise" category for our range and vision of cyber-security applications aimed at protecting critical patient data.

Application Presentation

It was announced on the 20th September that McKesson were successful in being shortlisted to the final four. James Hurley, Director of Engineering and Graham Baitson, Lead of Innovation Labs travelled to the Gibson Hotel, Dublin to present their submission and answer grilling questions on all aspects of the application from the judges.

Figure 2: AI Awards Large Enterprise Finalists and McKesson Presentation Team (Graham Baitson, Lead of Innovation Labs & James Hurley, Director of Engineering)

Award Ceremony

All the hard work had been done as it all boiled down to this moment. The moment that everyone had been waiting for. A packed house as over 200+ industry professionals, academics and enthusiasts came together to celebrate the very best of AI in Ireland at the inaugural AI Awards (AI Awards, 2018b). Three incredibly strong contenders, gripped to the edge of their seats, waiting to snatch victory from within our grasp. Our faith now rested in the opening of that precious gold envelope. But who will be the winner? We anxiously looked at each other during the famous "and the winner is" pause, of what felt like an eternity. MCKESSON !!!!! We had done it. We had won.

Figure 3: McKesson - 2018 Winners of the AI Awards "Best Application of AI in a Large Enterprise" Category (Graham Baitson, James Hurley, Amy Garde, Denis Canty, Glenn Fitzpatrick)

Top Comments

It was clear to see the hard work that the AI Awards team have put in to make this event a success. Their aspirations had come to fruition as the entire ceremony had gone precisely to plan. In addition to the awards, the event was filled with thought-provoking and inspirational talks. The following are some of my favourite moments.

Figure 4: Mark Kelly, Founder of AI Ireland

Figure 5: Cathriona Hallahan, Managing Director at Microsoft

Figure 6: James Hurley, Director of Engineering at McKesson

Figure 7: Una Fitzpatrick, Director of Technology Ireland - Ibec

Figure 8: Alessandra Sala, Head of Analytics Research at Nokia Bell Labs

Figure 9: Petronel Bigioi, SVP Engineering and GM at FotoNation

Figure 10: Orla Cullen, Product Management - Predictive Analytics at SAP

Figure 11: Ken Finnegan, Director of Innovation at Harbour Innovation Campus

McKesson Labs

We’re experiencing an era of unprecedented change in healthcare. New technology, new services and new ideas will be needed in order to deliver improved outcomes for businesses and patients. McKesson is at the forefront of that transformation.

Figure 12: 2018 McKesson Labs, Cork

Mission

Denis Canty, Senior Director of Engineering at the time, joined McKesson back in July 2017 with the ambition of creating a team to collaborate globally, maximise existing technologies and carry the flag of disruption to drive technology through the business. McKesson Labs had been born. McKesson Labs initially formed two technology hubs located in Cork, Ireland and Scottsdale, Arizona to focus on the pillars of innovation, design, developer services and automation products. McKesson Labs collaborate closely with cross-functional teams globally, partner with companies, engage with local universities and participate in conferences in order to understand and create products that reduce cost, drive revenue growth, and potentially create new revenue streams for McKesson.

AI Award Winning Application

As attackers start to utilise the vast array of complex tools and technologies that are available, cyber-attacks become more sophisticated, so much so, to the point where humans are struggling to identify safe from malicious data. McKesson feel that the integration of advanced technologies will enhance the security of patient critical data by accelerating the ability to distinguish and classify safe from malicious data.

By leveraging next-gen technology, ever-evolving intelligent solutions can be created with the aim to combat potential data breaches. By using a combination of software robotics, sentiment analysis and investigative computing, automation products can be developed to identify malicious threats and act as augmented AI sentinels. This ecosystem of cognitive agents can continue to strengthen McKesson's defence perimeter by dynamically controlling the various internal protection mechanisms. By complimenting the above with Human in the Loop (HITL) and smart reinforced tagging, the overall security hygiene can be vastly improved, increasing the capability for the detection and awareness of malicious data activity, thus reducing incident response times. This is a clear example of applying advanced AI technologies to compliment automation in delivering improved security posture for a Fortune 7 company, whilst also gaining financial savings.

2019 AI Awards

The deadline for applications is August 30th so make sure you get your submissions in to be in with a chance of winning. McKesson are delighted to show our continued support and support this year’s event, along with some great names.

Figure 13: 2019 AI Award Sponsors

In addition to sponsoring this year’s event, James Hurley, Director of Engineering and Graham Baitson, Lead of Innovation Labs are one of the judges for the 2019 AI Awards. We are really looking forward to being part of the experts panel in deciding this year’s winners.

Figure 14: 2019 AI Award Judges

Final Thoughts

On October 2018, Denis Canty was promoted to the Vice President of Technology Labs, and as a result, McKesson Labs continue to grow in numbers, talent, applications and also locations, adding hubs in Las Colinas, Texas and Alpharetta, Georgia. If you want to join the team and be part of this journey, then please have a look at the current open positions .

AI is paving the way to create applications that once seemed science fiction. But with these application comes the ethical implications that cannot be ignored. We are going to need the brightest minds to solve the future of the worlds problems and ensure that technology is used for the good of mankind. We are living in a challenging, exciting and also potentially scary time where there's so much uncertainty to what our future has to offer. It's important that we are all part of the future and have our say through our contributions. So until our next victory, Kathy McElligott, Executive VP, CIO / CTO of McKesson has perfectly described what can be achieved when hard work and determination meets collaboration.

"A perfect example of the innovation derived when great minds collaborate across teams and continents" - Kathy McElligott, Executive Vice President, Chief Information Officer / Chief Technology Officer at McKesson

References

AI Awards. (2018a). AI Awards. [online] Available at: https://aiawards.ie/about-us/
AI Awards. (2018b). AI Awards 2018: Six winners revealed at Sold-out Ceremony in Dublin. [online] Available at: https://aiawards.ie/ai-awards-2018-six-winners-revealed-at-sold-out-ceremony-in-dublin/
Figure 3: McKesson - 2018 Winners of the AI Awards "Best Application of AI in a Large Enterprise" Category (Graham Baitson, James Hurley, Amy Garde, Denis Canty, Glenn Fitzpatrick). Conor McCabe Photography.
Figure 4: Mark Kelly, Founder of AI Ireland. Conor McCabe Photography.
Figure 5: Cathriona Hallahan, Managing Director at Microsoft. Conor McCabe Photography.
Figure 6: James Hurley, Director of Engineering at McKesson. Conor McCabe Photography.
Figure 7: Una Fitzpatrick, Director of Technology Ireland - Ibec. Conor McCabe Photography.
Figure 8: Alessandra Sala, Head of Analytics Research at Nokia Bell Labs. Conor McCabe Photography.
Figure 9: Petronel Bigioi, SVP Engineering and GM at FotoNation. Conor McCabe Photography.
Figure 10: Orla Cullen, Product Management - Predictive Analytics at SAP. Conor McCabe Photography.
Figure 11: Ken Finnegan, Director of Innovation at Harbour Innovation Campus. Conor McCabe Photography.

RebelCon 2018 - Scaling Technology and Organizations Together

Sun, 19 May 2019 17:05:23 GMT

In the lead up to RebelCon 2019, here are my notes from the 'Scaling Technology and Organizations Together' workshop I attended last year. All thoughts, views and opinions are my own.

RebelCon Overview

RebelCon is Ireland’s largest Software Engineering conference, which brings together the Cork software engineering community over 2 days of workshops and talks on the latest technology, culture and development practices in the software industry. For more information, visit http://rebelcon.io/ .

2018 Conference Overview

McKesson were a proud sponsor of RebelCon 2018, which took place on Thursday 21st June and Friday 22nd June 2018 at The Clayton Hotel, Cork City. I attended the "Scaling Technology and Organizations Together" Workshop, presented by Randy Shoup, VP Engineering at WeWork, previously eBay and Google. The following are my notes from the workshop.

Scaling an Organisation

Main Notes

Break large teams into small dedicated teams
Move from waterfall (idea → develop → quality → operations) to full-stack teams
Align teams to business problems by creating clear goals and metrics → this will result in teams growing by "cellular mitosis"
Create small "service" teams. Create a symphony not a factory
An ownership of software gives incentive to do the job well → this will result in reduced maintenance
Half-remote teams and also half co-located teams just don't work → aim for full either remote or located teams

Side Notes

Amdahl's law - https://en.wikipedia.org/wiki/Amdahl%27s_law
Mel Conway, Extreme Prototyping - https://www.ustream.tv/recorded/114861629
Jeff Bezos' 2 Pizza Rule - https://blog.bufferapp.com/small-teams-why-startups-often-win-against-google-and-facebook-the-science-behind-why-smaller-teams-get-more-done
Google has 30,000 engineering people and can still innovate because each team has their own goals, objectives, etc...

Scaling a Development Process

Main Notes

Deploy small units of work → easier to fix problems, easier to roll-back/roll-forward
Understand that other business teams may not have the training in the discipline of problem solving, context and implications → try and help people analyse and think about the problem they are trying to solve when they come to you with a solution (e.g. if they ask you to add a UI button, try and understand that the problem is as it could be solved by something simpler)
"Fewer things, more done" → get smaller features done with extra resources and release earlier (e.g. rather than having 5 iterations with 5 features to finish at last iteration with 1 person per feature, aim for regular feature releases by assigning more people to the features)
Quality and reliability are priority
Build one great thing instead of two half-finished things
Done right does not equal done perfect → aim for the 80/20 rule - https://en.wikipedia.org/wiki/Pareto_principle

Side Notes

Book recommendation: DevOps Handbook - https://www.amazon.co.uk/Devops-Handbook-World-Class-Reliability-Organizations/dp/1942788002
Book recommendation: Lean Software Development - https://www.amazon.co.uk/Lean-Software-Development-Toolkit-Managers/dp/0321150783
Book recommendation: Making Work Visible - https://www.amazon.co.uk/Making-Work-Visible-Exposing-Optimize/dp/1942788150/
"A problem well stated is a problem half solved" - Charles Kettering
If there are bottlenecks in your code during collaboration, allow other teams to suggest and make patches to your codebase
Have a backlog of small items, that you generally wouldn't get a chance to work on and that are not high priority. At times when work is light and people are looking for something to work on, they can pull from this backlog.

Topic: Scaling an Architecture

Main Notes

Rearchitecting a system is a sign of success not failure
When attempting to migrate a system, choose a vertical slice (that goes through all the layers from start to finish) to rebuild → don't rebuild horizontally because then the value only comes at the end and it's much harder

Side Notes

eBay are now on their 5th rewrite/generation of codebase (Monolithic perl → monolithic C++ → java → micro-services). During the eBay C++ monolithic stage, they were hitting limits on the number of maximum methods allowed per class and had approximately 3.4 million lines of code in a DLL
Twitter are now on their 3rd rewrite/generation of codebase (Monolithic rails → js/rails/scala → micro-services)
Amazon are now on their Nth rewrite/generation of codebase (Monolithic perl → C# → java/scala → micro-services)
Book recommendation: Working Effectively with Legacy Code - https://www.amazon.co.uk/Working-Effectively-Legacy-Michael-Feathers/dp/0131177052 . This book is supposedly on the Google engineers required listing.

2018 Speakers Comments

The following are some of the speaker’s comments from after the event (RebelCon, 2019).

Figure 1: Melissa Perri, CEO of Produx Labs, Author of Escaping the Build Trap

Figure 2: Randy Shoup, VP Engineering at WeWork

Figure 3: Sam Newman, Author of Building Microservices

References

RebelCon. (2019). RebelCon. [online] Available at: http://rebelcon.io/
Figure 1: Melissa Perri, CEO of Produx Labs, Author of Escaping the Build Trap. [online] Available at: https://miro.medium.com/max/2400/1*Mk8z1-qei_8Ta2dJvbQ1Ng.jpeg
Figure 2: Randy Shoup, VP Engineering at WeWork. [online] Available at: https://miro.medium.com/max/2400/0*knso_FIw9AWuYgYm.jpeg
Figure 3: Sam Newman, Author of Building Microservices. [online] Available at: https://wizeline-website-assets.s3.amazonaws.com/wp-content/uploads/sites/8/2018/09/27113312/Screen-Shot-2018-09-27-at-1.31.44-PM.png

Microsoft Paint – For the AI Generation

Thu, 21 Mar 2019 17:53:48 GMT

3 minute read

One of the many talents that I wish I had and unfortunately was not blessed with is the ability to draw realistically. As a kid, I was obsessed with colouring books, patterns and drawing. I used to record the TV screen using the VHS video player (yes this was before the dawn of Netflix and DVD) and then try to recreate what was on the screen. Needless to say, none of them were any good and I don’t have any masterpieces hanging in any galleries around the world. But, with the help of the latest developments from Nvidia Research, I now get to see my ’masterpieces’ come to life.

GauGAN – From Doodles to Works of Art

This week at the Nvidia GPU Technology Conference (GTC) 2019, Nvidia unveiled their latest image processing research efforts, and it’s pretty incredible. Trained using 1 million images on Flickr (Burns, M., 2019) and leveraging generative adversarial networks (GANs), the deep learning model transforms basic segmentation maps into highly realistic images.

Video 01: GauGAN

The software allows you to draw an images using basic shapes, and then with the inclusion of labelling, be able to transform those shapes into realistic landscape imagery. In addition, it also has the built-in awareness of what has been generated within the scene, allowing the image to dynamically adapt to the other textures. For example, if you have an image of a green leafy tree on a summers day and then label the ground as snow, the tree will convert to barren. If you then introduce a lake, the tree and nearby elements will automatically be reflected in the water.

“ It’s like a coloring book picture that describes where a tree is, where the sun is, where the sky is…and then the neural network is able to fill in all of the detail and texture, and the reflections, shadows and colors, based on what it has learned about real images” - Bryan Catanzaro, VP of Applied Deep Learning Research, Nvidia

Going, Going, GAN

Invented in 2014, GANs contain the potential to learn the natural features of a dataset, resulting in the ability to imitate any distribution of data. The concept takes two cooperating neural networks; a generator and a discriminator. The Discriminator is initially trained on real data to produce a blueprint of what a real image should look like. The Generator then produces new data instances and presents them to the discriminator. The Discriminator then evaluates the authenticity by comparing the sample to its blueprint. The Discriminator provides feedback to the Generator on how to improve the realism of its synthetic images. Both work together to improve each other’s function (i.e. Generator is improving at creating realistic images and Discriminator is improving at detecting them).

Virtual Worlds

This approach has the potential to completely transform the creation of scenic environments. Not only does allow people who may not be highly skilled start creating realistic scenery, but also allows the professionals to focus more of their efforts on prototyping more interesting sceneries and making quicker changes more efficiently. This powerful tool could have potential applications in architecture, landscaping, game designing and even film making. Although GauGAN at present focuses purely on natural elements like rocks, land and sea, “the underlying neural network is capable of filling in other landscape features, including buildings, roads and people” (Nvidia, 2019). With over 170 full-time researchers and in 2018, rolling out 104 publications, 51 patent applications and 12 open-source software packages (Medium, 2019), I really interested to see what further developments are made in this space.

More Information

The following are more links if you need further information

NVidias’ AI Playground: https://www.nvidia.com/en-us/research/ai-playground/
GauGAN Project Website: https://nvlabs.github.io/SPADE/
GauGAN Research Paper: https://arxiv.org/abs/1903.07291
GauGAN Code: https://github.com/NVLabs/SPADE

References

Burns, M., (2019). Fdsfds. Available at: https://techcrunch.com/2019/03/18/nvidia-ai-turns-sketches-into-photorealistic-landscapes-in-seconds/ . [Accessed 20 March 2019].
Figure Cover: https://blogs.nvidia.com/blog/2019/03/18/gaugan-photorealistic-landscapes-nvidia-research/
Medium (2019). GTC 2019 | NVIDIA’s New GauGAN Transforms Sketches Into Realistic Images. Available at: https://medium.com/syncedreview/gtc-2019-nvidias-new-gaugan-transforms-sketches-into-realistic-images-a0a74d668ef8 . [Accessed 20 March 2019]
Nvidia (2019). Stroke of Genius: GauGAN Turns Doodles into Stunning, Photorealistic Landscapes. Available at https://blogs.nvidia.com/blog/2019/03/18/gaugan-photorealistic-landscapes-nvidia-research . [Accessed 19 March 2019].
Video 01: GauGAN. Available at: https://youtu.be/p5U4NgVGAwg . [Accessed 19 March].
Wolfe, J. (2019). Stroke of Genius: NVIDIA Researchers Debut GauGAN at GTC 2019. Available at: https://www.awn.com/news/stroke-genius-nvidia-researchers-debut-gaugan-gtc-2019 . [Accessed 20 March 2019].

Are Humans the Next Horse? The Rise of the Robots

Tue, 19 Mar 2019 12:46:17 GMT

6 minute read

Just over a week ago I attended the AI & Machine Learning Summit in Dublin and it was evident that we have now entered an era of unchartered territory. The science fiction of our youth, is no longer science fiction. The ‘robot revolution’ is on our doorstep and we need to start preparing. So should we pack our bags and head to the forest for a life of solitude, or should we hold up our welcome signs to the robot successors?

The Impact of the Industrial Revolutions

In Greek mythology, the Titan Prometheus had a reputation of being wise and gifted with foresight, a skill that was considered to be needed for the near future at the time. As the story goes, Prometheus, who was known to be quite the trickster, stole fire from the gods in order to equip mankind with the necessary tools that would make them formidable against the beasts of the earth. Fire allowed them to build civilisations by crafting weapons, cooking food and surviving the cold winters. Since this gift of fire was bestowed, mankind has been entering waves of innovations throughout their evolution to improve their standard of life. Let’s take a quick nosedive into the history of the disruptive innovation.

Steam Power - First Industrial Revolution (1784)

The steam engine was quite arguably the most crucial invention to the industrialisation of model civilisation. Horses were originally used to transport goods, but were quite expensive, limited in terms of the load they could carry and also required a lot of care to keep them in good shape (Whipps, 2008). The introduction of steam power gradually displaced the need for using horses, showing a decline of nearly 88% over the course of a half century (Brynjolfsson, E. & Mcafee, A., 2015) and resulted in a 0.5% salary increase between 1782 and 1857, higher employment rates and a 5% improvement in the standard of living between 1780 and 1850 (Feinstein, 1998).

Electricity & Mass Production - Second Industrial Revolution (1870)

A century later dawned the age of perhaps the most prolific period in terms of changes to the modern world. A new source of energy emerged (i.e. electricity, gas and oil), resulting in growing cities and the creation of factory jobs. Henry Ford, one of the most imperative inventors of the industrial revolutions, used this combination of energy to its full potential. Completely transforming transport, Ford created the Model T in 1908, a car that was powered by a gasoline engine and build within a factory assembly line. This period completely transformed people’s lives with the rapid advances in the creation of steel, chemicals and electricity resulting in better more comfortable lives and cheaper mass productions for tools, weapons, transport and media (Niiler, 2019).

Digital & Automation - Third Industrial Revolution (1969)

Stepping forward another century, advances in digital communications has forever changed the way we transmit information, how we do business and how we interact with each other (Niiler, 2019). With the emergence of yet another form of energy (i.e. nuclear) and the move from analog to digital, electronics and information technology began to automate production and take supply chains global (Trailhead, 2019).

AI – Fourth Industrial Revolution (2000+)

We are currently living through a revolution that has the ability to completely redefine who we are as humans. Humans are no longer distinct from technology, but are now augmented by technology, devices and sensors. There are endless possibilities to create unimaginable innovations by combining advanced biotechnology, robotics and artificial intelligence, to name but a few. In one of my previous articles, ‘ Web Summit 2018 – My Best of the Rest ’, I talked about autonomous vehicles and the ethical implications associated. All these technological advancements are challenging our interpretations of life and consciousness.

The Impact of AI on Future Growth

There is a common theory that history tends to repeat itself. If we look at the previous industrial revolutions, people were worried about losing jobs and “social critics were fearful about the loss of freedom, autonomy and independence being replaced by boredom and repetition” (Niiler, 2019). All of which were disproven at the fact that for the majority, each advancement in human evolution has brought with it better quality of life and more jobs. But what’s different this time around? Well this is the first time that we are potentially on the cusp of being the creators of own extinction.

"The development of full artificial intelligence could spell the end of the human race….. Humans, who are limited by slow biological evolution, couldn't compete, and would be superseded" – Professor Stephen Hawking

Technology is advancing faster than we can shake a stick at. Robots can now navigate through mazes, climb obstacles and do backflips (Youtube – Wired, 2018), whereas I struggle to do a burpee without fear of pulling a muscle. Netflix has a great film AlphaGo, which shows the progression of artificial intelligence in the quest to conquer the ancient Chinese boardgame Go, a boardgame that has more possible configurations than there are atoms in the observable universe (Netflix – AlphaGo, 2017) and has long been considered to be one of the most difficult challenges for AI. The HBO show Westworld then combines both the robotics and the AI to bring a face to the technology by showing what a world could look like when an AI Android becomes indistinguishable from a human. (HBO – Westworld, 2016).

There was two main themes which resonated across all talks from the AI Summit; education and ethics. Estimated to contribute to as much as $15.7 trillion to the global economy by 2030 (AISummit, 2019), how do we share preparing for this advancement in AI?

Education: Shift from Left-Brain to Right-Brain

It is becoming more and more apparent that we must concentrate and focus on preparing the youth of day for the careers of tomorrow. If you listen to Sir. Ken Robinson, he has done incredible work on trying to change the education paradigm in order to allow kids to flourish in what was predominantly a head-on approach to education. Not every child learns in the same way and the curriculum is not currently setup in a way to allow kids to flourish in their creative elements.

“The educational system needs to evolve from a predominantly focused left-brain curriculum to a right-brain one in order to allow for creative diversity in the future workforce” – Denis Canty, VP of Technology Labs, McKesson.

As we move towards the workforce of the future, it is becoming ever more critical to obtain the most from a child’s natural interests and ability. These creative and innovative elements will be crucial to a sustainable workforce and being able to work alongside the AI of the future. In addition to being able to identify patterns and anomalies, one of the biggest benefits that machine leaning (ML) and AI bring is the ability to perform low-level repetitive and tedious tasks. Therefore jobs that purely rely on these types of tasks will most definitely be displaced with the advancements in technologies, but on the other hand, it will alleviate humans to focus on more higher-level functions and meaningful tasks.

“The jobs of the future will be high tech and high touch... and the soft skills of today (e.g. creativity, empathy, leadership), will be the hard skills of tomorrow” - Paul Healy, Chief Executive of Skillnet Ireland.

Ethics: Does AI Have a Face?

For the first time in history, technology is touching almost everyone’s lives. As a result, it is becoming impossible to predict what type of impact these advancements are going to have on humankind.

“AI today is becoming less of a technology problem and more of a humanities problem... what is the environmental cost of AI” – Barry O’Sullivan, Founding Director, Insight, UCC.

There are a number of research studies done around the debate of whether modern technology will have a positive or negative effect on the health, well-being and future of humans. With almost everything we use in everyday life, there’s an option to use it for good or use it for bad. It is inevitable that there will be consequences of AI that will have a negative impact but it is critical that ethics is embedded and at the forefront of the development of the applications that are created.

“Our generation has inherited more opportunities to transform the world than any other. That’s a cause for optimism, but only if we’re mindful of our choices” - Erik Brynjolfsson and Andrew McAfee, The Second Machine Age

Final Thoughts

A common outcome from each of the previous revolutions is one of major societal transformations. With each new wave of inventions comes a fundamental change on how people live, work and communicate. We are currently taking part in what seems to be an exponential advancement of technology that is distorting the boundary of our biological, digital and physical worlds. AI can now diagnose medical conditions with higher accuracy than experts, navigate cars with less chance of being involved in a collision and have a conversation with us as if they were a human. Back in 2017, Facebook had to stop an experiment as two of their artificial intelligence chatbots seemed to start talking to each other using language that only they could understand.

We are moving at pace towards the singularity; the moment where artificial intelligence bypasses that of human intelligence. Will we ever get there and how will we know when this happens? It is becoming more and more impossible to predict how this one is going to turn out. Looking back just over 10 years ago, there was no iPhone, no Instagram, no Spotify. A decade in current technology terms has now become a portion of time where literally anything could happen. There’s uncertainty on agreement between the worlds brightest minds. Yes, certain tasks will be automated. Yes, certain jobs will be lost. Yes, certain professions will become redundant. But with this change will come great opportunity. A chance to understand what it is that truly makes us human.

Until next time, I hope you enjoyed the read. GB

References

Brynjolfsson, E. & Mcafee, A. (2015). Will humans go the way of horse labor?. Available at: https://www.dallasnews.com/opinion/commentary/2015/10/09/brynjolfsson-and-mcafee-will-humans-go-the-way-of-horse-labor . [Accessed 17 March 2019]
The Dualarity (2016). The Industrial Revolution 4.0. Available at: https://www.thedualarity.com/industrial-revolution-4-0-2/ . [Accessed 9 March 2019]
Feinstein, C. (1998). Pessimism Perpetuated: Real Wages and the Standard of Living in Britain during and after the Industrial Revolution. The Journal of Economic History, 58(3), 625-658. [online] JSTOR. Available http://www.jstor.org/stable/2566618 [Accessed 27 Nov. 2017].
Figure Cover: https://www.youtube.com/watch?v=7c_XO3Ouzts
HBO – Westworld (2016). Westworld. Available at: https://www.hbo.com/westworld . [Accessed 15 November 2017].
Netflix – AlphaGo (2017). AlphaGo. Available at: https://www.netflix.com/ie/title/80190844 . [Accessed 14 March 2019).
Niiler, E. (2019). How the Second Industrial Revolution Changed Americans' Lives. Available at: https://www.history.com/news/second-industrial-revolution-advances . [Accessed 16 March 2019].
Sentryo (2017). The 4 Industrial Revolutions. Available at: https://www.sentryo.net/the-4-industrial-revolutions/ . [Accessed 9 March 2019]
Simon, Herbert A. (1986). The Steam Engine and the Computer: What Makes Technology Revolutionary. EDUCOM '86 Conference, November 12, 1986. Available online at: http://digitalcollections.library.cmu.edu/awweb/awarchive?type=file&item=34057
Trailhead (2019). Meet the Three Industrial Revolutions. Available at: https://trailhead.salesforce.com/en/content/learn/modules/learn-about-the-fourth-industrial-revolution/meet-the-three-industrial-revolutions . [Accessed 9 March 2019].
YouTube - Wired (2008). How Boston Dynamic’s Robots Became Internet Favorites | WIRED. Available at: https://www.youtube.com/watch?v=hMtABzjslXA [Accessed 9 March 2019]
Whipps, Heather. (2008). How the Steam Engine Change the World. Available at: https://www.livescience.com/2612-steam-engine-changed-world.html . [Accessed 9 March 2019]

The Human-Centered Design Approach

Mon, 25 Feb 2019 20:42:06 GMT

In my recent article ' Why You Should Thank Leonardo da Vinci - An Overview of User Experience (UX) Design ', I took a look at the origin of UX design, the progression over time and then how it can be broke down into its simplest elements. This article builds on these concepts by outlining some of the steps used to conduct a human-centered design project. All thoughts, views and comments are my own.

Introduction

HCD is a creative approach to solving problems by involving the users perspective at every point along the journey. By implementing this approach and focusing on the user, the aim is to end up with an innovative solution that has been designed specifically to meet the demands of the user.

“Human-centered design is all about building a deep empathy with the people you’re designing for; generating tons of ideas; building a bunch of prototypes; sharing what you’ve made with the people you’re designing for; and eventually putting your innovative new solution out in the world.” [DesignKit, 2014]

The following are some steps that can be taken to ensure that the end-user is at the core of the design decision process.

Problem Identification

The identification of the problem is the first and foremost step in any research process. The Kenya Projects Organisation states research as a problem or unclear situation “which a researcher experiences in practical or theoretical context and wants to obtain a tangible explanation, clarification or offer solution to it” [Kenpro, 2012]. When it comes to designing an interface, the user experience is a fundamental ingredient to the survival length for the associated subject matter (e.g. application, lift/elevator, ATM machine). During the problem identification phase, it is imperative to identify areas that can be improved, and as a result, create an enriched user experience, enabling the interface to appeal to more users.

Figure 1: Problem Identification

Problem Justification

Figure 2: Problem Justification

Albert Einstein is attributed to saying that if he had one hour to solve a problem, he would spend the first 55 minutes defining the problem and the last 5 minutes thinking about the solutions. The justification of the problem is a critical phase in any process to ensure that all aspects of the problem have been thought about, justifying the need for a solution. One approach to verifying the problem statement is to perform a heuristic evaluation. This involves performing a usability inspection to identify problems based on compliance with recognised usability principles. One of the best known sources and most widely used set of heuristics are the ten proposed by Jakob Nielsen. These are based on an analysis of 249 usability problems.

Figure 3 Nielsen's Heuristics

1. Aesthetic and Minimalist Design

“Dialogues should not contain information which is irrelevant or rarely needed. Every extra unit of information in a dialogue competes with the relevant units of information and diminishes their relative visibility” [Nielson, J., 1995].

2. Match Between System and Real World

“The system should speak the users' language, with words, phrases and concepts familiar to the user, rather than system-oriented terms. Follow real-world conventions, making information appear in a natural and logical order” [Nielson, J., 1995].

3. Recognition Rather Than Recall

It is widely known that when it comes to the human memory, the performance of memory recognition is far greater than the performance of memory recall. The reason for this is based on the fact that there is a greater amount of cues that can help memory retrieval when it comes to recognition rather than recall. In the 'Psychology of Everyday Things', Norman looks at the cognitive load on memory when it comes to the concept of 'Knowledge in the head and in the world' [Norman, D. A., 1988].

“Minimize the user's memory load by making objects, actions, and options visible. The user should not have to remember information from one part of the dialogue to another. Instructions for use of the system should be visible or easily retrievable whenever appropriate” [Nielson, J., 1995].

4. Consistency and Standards

When it comes to designing an interface, visual consistency and standards play a vital role for a number of reasons. It increases the usability which will in turn attract and maintain users. It makes it easy for uses to access the most important information in a quick and intuitive manner. Finally, consistency evokes a strong emotional response [Anić, I., 2015]. There are a number of different ways to achieve this consistency from using similar colours, providing navigation menus and using similar icons, links and form elements throughout the site [Lacey Tech Solutions, 2013].

“Users should not have to wonder whether different words, situations, or actions mean the same thing” [Nielson, J., 1995].

5. Visibility of System Status

The system status and feedback give the user an indication on the progress and completion of their actions. The system status can include the current location within the application, the progress towards completion and also the time needed for a task to be completed [UTHealth, 2016].

“The system should always keep users informed about what is going on, through appropriate feedback within reasonable time” [Nielson, J., 1995].

6. User Control and Freedom

It's essential that a user feels in control during their experience of using an interface. If they should land on a page and want to return to where they came from, there should be clear navigation options regardless of where they reside within the system. If there are no clear signs on navigation, they will most likely become frustrated with their poor experience of using the application and proceed to an alternate choice.

“Users often choose system functions by mistake and will need a clearly marked "emergency exit" to leave the unwanted state without having to go through an extended dialogue. Support undo and redo” [Nielson, J., 1995].

7. Flexibility and Efficiency of Use

“Accelerators -- unseen by the novice user -- may often speed up the interaction for the expert user such that the system can cater to both inexperienced and experienced users. Allow users to tailor frequent actions” [Nielson, J., 1995].

8. Help Users Recognise, Diagnose and Recover From Errors

“Error messages should be expressed in plain language (no codes), precisely indicate the problem, and constructively suggest a solution” [Nielson, J., 1995].

9. Error Prevention

Providing the user with feedback if errors should occur is an important part of gaining trust with the user at times of unusual circumstances. This feedback should be informative and explain to the user what has happened and how to resolve the potential issue.

“Even better than good error messages is a careful design which prevents a problem from occurring in the first place. Either eliminate error-prone conditions or check for them and present users with a confirmation option before they commit to the action” [Nielson, J., 1995].

10. Help and Documentation

“Even though it is better if the system can be used without documentation, it may be necessary to provide help and documentation. Any such information should be easy to search, focused on the user's task, list concrete steps to be carried out, and not be too large” [Nielson, J., 1995].

Affinity/Empathy Mapping

Figure 4: Affinity/Empathy Mapping

An affinity diagram is a powerful technique that can be used to sort and group large amounts of data in order to visualise and understand it more effectively. The process is quite simple and straightforward requiring each user to write terms related to how they feel a user interacts with the interface. These terms should be aligned to a number of categories, combined and grouped obtaining a consensus on how the interface information should be structured and displayed [InfoDesign, 2016].

Figure 5: Affinity/Empathy Mapping Example

Proto-Persona Creation

Figure 6: Proto-Persona Creation

Proto-personas are a great way to ensure that design decisions are based on an educated guess to who the end users for the interface is designed for [Ilama, E., 2015]. It's also an excellent way to redirect the focus throughout the project, from the interface to the end user, ensuring that at every stage, all the correct design and functionality decisions are made [Summers, B., 2016].

Figure 7: Proto-Persona Example

User Research - Questionnaire

In UX, questionnaires are a relatively quick and cheap way to gather information on the users "preferences, attitudes, characteristics and options" when it comes to understanding what the user is looking for, how they would most likely use and what the most important aspects of an interface would be [Gray, 2014]. This information is extremely beneficial for designers when working on implementing prototypes to provide the required functionality. The information obtained from these questionnaires and surveys relate to a subset of a population, the learnings of which can be then applied to the broader population.

Figure 8: User Research - Questionnaire

User Research - Interviews

Performing an interview after an online survey allows to further clarify and explain the survey answers [Veal, R., 2016]. When preparing for the interviews, it is important to identify potential user groups and then spend time providing an interview script with an explanation/introduction on why the interview is taking place, along with the main goals and questions that need to be addressed [Mears, C., 2013]. The ideal outcome from the interviews should be to uncover any concerns and misunderstanding from the user by qualitatively discovering a user’s attitude, beliefs and experience towards an interface, whether it be associated with a product or an application, by capturing their emotions and body language [Veal, R., 2016].

Figure 9: User Research - Interviews

User Research - Observation

While observing a user, it is important to give them some meaningful tasks to perform [Nielsen, N., 2014]. "There's nothing more impactful than seeing people perform their tasks and encounter problems firsthand. Observation promotes empathy for users and the problems they face" [Ross, J., 2012].

Figure 10: User Research - Observation

User Research - Results Filtering

When gathering data from online surveys, interviews and observations, it is vital that this data is then analysed in order to get an overall impression and understanding of the subjects data.

Figure 11: User Research - Result Filtering

Task Descriptions

Figure 12: Task Descriptions

Task descriptions are a great way to incorporate the research data into something tangible, related to the type of users, how they will be interacting with the system and what functionality should be facilitated by the interface [Errity, A. & Reardon, S., 2016]. These task descriptions can be broken down into a number of different elements, each with their own benefits and their own way of gathering and structuring the data obtained from research. Without research, an understanding of your users and proper direction, interfaces increase in the risk of falling into the tyre swing analogy [Ward, J., 2010].

Figure 13: The Tyre Swing Analogy

Typically, the three main activities that fall under task descriptions are; user stories, scenarios and storyboards.

User Stories

A user story is presented in a user-centric way that "encapsulates a need or piece of functionality in the language of the end user, that sums up what the requirement or goal is and the reason for it" [Mears, C., 2013]. User stories originated from the advancement of agile and scrum methodologies, aimed at allowing designers and developers to prioritise and organise how each piece of functionality should be designed and created [Brinton, B., 2015].

Scenarios

A scenario is a narrative story that gives a background to the user and why they are going to visit the interface and "are typically used to provide a picture of the intended user experience" [UXM, 2010].

Storyboards

A storyboard is a sequential flow of images that are used to visualise and bring a vision to life. These are used to provide an overview of a scenario in an engaging way that people can understand [Crothers, B., 2011]. Storyboards help outline any issues that could arise while performing a range of functions, resulting in strengthening the user experience elements of a design [Little, A., 2013].

Persona Creation

A persona, who is referred to as a hypothetical person, is created based on the research data obtained from observing and gathering information from many people. As it is highly unlikely to cater for all types of users in a system, a persona represents a significant portion allowing designers and engineers to focus on creating functionality and implementing design elements aimed at the majority [Goltz, S., 2014].

Personas originate back to the early 80's when Alan Cooper wanted to try and empathise with the users that were using the software that he had designed and created. He understood that in order to be successful and persuade clients, he needed to help clients see the world from the users perspective [Goltz, S., 2014].

Figure 14: Persona Creation

Prototyping

Prototyping allows functionality flow and proposed designs to be tested before going through the entire design process of implementing expensive wire-frames. Users can quickly test ideas and then give feedback based on their interactions with the designed prototypes.

Figure 15: Prototyping

Goals

When it comes to UX, goals are based on the combination of an understanding of the interfaces users along with the business requirements for the interface [Errity, A. & Reardon, S., 2016]. Goals can be split into two contrasting categories, qualitative and quantitative, both of which have their strengths and limitations when used solely without the consideration of the other. Qualitative goals are very much subjective towards emotional based responses, which are extremely useful in guiding initial and iterative design efforts. The feedback obtained from these qualitative goals "tells 'why' at a level that quantitative data cannot reveal" [TryMyUI, 2016]. Quantitative goals are measurable responses that are based on facts and performance. The feedback obtained from these quantitative goals "strengthen and justify qualitative findings" and can be used to "set predictable objectives for a new design sprint" [TryMyUI, 2016].

Figure 16: Goals

Prototype User Testing

Prototypes are used in order to receive user feedback at the early stages of developing an interface in order to assess the viability of a design [UserTesting, 2016]. Feedback can be based on a number of different aspects of the interface including learnability, efficiency of use, memorability, errors and satisfaction [Errity, A. & Reardon, S., 2016]. It is critical to make research-backed, user-centered decisions at the beginning of the process. It is estimated that 50% of engineering time is spent doing rework that could have been avoided [Usability, 2016] and that fixing an error after development has been completed is up to 100 times as expensive as it would have been before [Weinschenk, S., 2011].

Figure 17: Prototype User Testing

Conclusion

The experience a user takes when using an interface is clearly a vital role in the retention rate for that user interface. It is said that if the user interface has not been designed in a way that makes it easy for the user to navigate, find the most important information and interact with the features it provides, they will leave within 15 seconds. By taking a human-centered approach when designing, you can maximise your chance of capturing the user’s attention within 15 seconds and “know that your solution will be a success because you’ve kept the very people you’re looking to serve at the heart of the process.” [DesignKit, 2014].

References

Anić, I. (2015). The importance of Visual Consistency in UI Design. [ONLINE] Available at: http://www.uxpassion.com/blog/the-importance-of-visual-consistency-in-ui-design/ . [Accessed 17 February 2019].
Brinton, B. (2015). User Stories: A Foundation for UI Design. [ONLINE] Available at: http://www.uxbooth.com/articles/user-stories-a-foundation-for-ui-design/ . [Accessed 17 February 2019].
CrazyEgg (2018). The 15 Second Rule: 3 Reasons Why Users Leave a Website. [ONLINE] Available at: https://www.crazyegg.com/blog/why-users-leave-a-website/ . [Accessed 22 February 2019]
Crothers, B. (2011). Storyboarding & UX – part 1: an introduction. [ONLINE] Available at: http://johnnyholland.org/2011/10/storyboarding-ux-part-1-an-introduction/ . [Accessed 17 February 2019].
DesignKit (2014). What is Human-Centered Design? [ONLINE] Available at: http://www.designkit.org/human-centered-design . [Accessed 22 February 2019]
Errity, A. & Reardon, S. (2016). Goal Setting. [ONLINE] Available at: https://www.dropbox.com/sh/vp3puz814w7ery4/AAAD8Cj2uFJQ4eZEcFXbp15Ga/Day%204?dl=0&preview=9+-+Goal+Setting.pdf . [Accessed 17 February 2019].
Errity, A. & Reardon, S. (2016). Task Modelling. [ONLINE] Available at: https://www.dropbox.com/sh/vp3puz814w7ery4/AABa6Y40IGz-6XKh-3VEVBN1a/Day%202?dl=0&preview=5+-+Task+Modelling.pdf . [Accessed 17 February 2019].
Errity, A. & Reardon, S. (2016). User Testing. [ONLINE] Available at: https://www.dropbox.com/sh/vp3puz814w7ery4/AAAD8Cj2uFJQ4eZEcFXbp15Ga/Day%204?dl=0&preview=10+-+User+Testing.pdf . [Accessed 17 February 2019].
Figure 1: Problem Identification. http://www.hdwallpapers.in/walls/wall_e__rubiks_cube-wide.jpg
Figure 2: Problem Justification. http://answersafrica.com/wp-content/uploads/2015/07/shutterstock_Symbol-of-law-and-justice-1.jpg
Figure 3: Nielsen's Heuristics. https://www.dropbox.com/sh/vp3puz814w7ery4/AACoNXCA_HtBWtjW1VhO_qIBa/Day%203/8%20-%20Heuristic%20Evaluation.pdf?dl=0
Figure 4: Affinity/Empathy Mapping. https://www.dialog-direct.com/atlas/wp-content/uploads/2015/04/paper-chain-people2.jpg
Figure 5: Affinity/Empathy Mapping Example. https://media.nngroup.com/media/editor/2017/11/07/screen-shot-2017-11-07-at-74041-am.png
Figure 6: Proto-Persona Creation. https://static1.squarespace.com/static/52737a77e4b08d0d31723765/52b01c1fe4b0880660ab27c9/57616b2a2eeb8180041b277f/1474466738411/Persona-3.jpg?format=1500w
Figure 7: Proto-Persona Example. https://venngage-wordpress.s3.amazonaws.com/uploads/2018/03/user-persona-examples-8.jpg
Figure 8: User Research - Questionnaire. http://www.boostbusinesssupport.com/wordpress/wp-content/uploads/2012/09/Questionnaire1.jpg
Figure 9: User Research - Interviews. http://i.huffpost.com/gen/1641782/images/o-JOB-INTERVIEW-facebook.jpg
Figure 10: User Research - Observation. https://aos.iacpublishinglabs.com/question/aq/1400px-788px/systematic-observation-psychology_62ca7bb505ed13ff.jpg?domain=cx.aos.ask.com
Figure 11: User Research - Result Filtering. https://www.collegeboard.org/sites/default/files/images/Home_Illustration_1.png
Figure 12: Task Descriptions. http://blog.appliedinformaticsinc.com/wp-content/uploads/2015/07/plan-well.jpg
Figure 13: The Tyre Swing Analogy. http://www.tamingdata.com/2010/07/08/the-project-management-tree-swing-cartoon-past-and-present/
Figure 14: Persona Creation. http://www.studioone.com/wp-content/uploads/2015/06/Buyer-Persona.jpg
Figure 15: Prototyping. https://s-media-cache-ak0.pinimg.com/originals/af/2e/4e/af2e4e2856886b5b6f4bf5c30562c2a5.jpg
Figure 16: Goals. https://assets-production-webvanta-com.s3-us-west-2.amazonaws.com/000000/49/06/original/archives/images/dart-targets.jpg
Figure 17: Prototype User Testing. http://help.usertesting.com/customer/portal/articles/1742260-prototype-testing
Goltz, S. (2014). A Closer Look At Personas: What They Are And How They Work (Part 1). [ONLINE] Available at: https://www.smashingmagazine.com/2014/08/a-closer-look-at-personas-part-1/ . [Accessed 17 February 2019].
Gray (2014). Better User Research Through Surveys. [ONLINE] Available at: http://uxmastery.com/better-user-research-through-surveys/ . [Accessed 17 February 2019].
Ilama, E. (2015). Creating Personas. [ONLINE] Available at: http://www.uxbooth.com/articles/creating-personas/ . [Accessed 17 February 2019].
Kenpro (2012). Topic Identification. [ONLINE] Available at: http://www.kenpro.org/topicidentification.htm . [Accessed 17 February 2019].
InfoDesign (2016). Affinity diagramming. [ONLINE] Available at: http://infodesign.com.au/usabilityresources/affinitydiagramming/ . [Accessed 17 February 2019].
Lacey Tech Solutions (2013). Why is consistency important in Web Design? [ONLINE] Available at: https://laceytechsolutions.co.uk/blog/importance-of-consistency-in-web-design/ . [Accessed 17 February 2019].
Little, A. (2013). Storyboarding in the Software Design Process. [ONLINE] Available at: https://uxmag.com/articles/storyboarding-in-the-software-design-process . [Accessed 17 February 2019].
Mears, C. (2013). User Interviews – The Beginner's Guide. [ONLINE] Available at: http://theuxreview.co.uk/user-interviews-the-beginners-guide/ . [Accessed 17 February 2019].
Nielsen, N. (2014). Turn User Goals into Task Scenarios for Usability Testing. [ONLINE] Available at: https://www.nngroup.com/articles/task-scenarios-usability-testing/ . [Accessed 17 February 2019].
Nielson, J. (1995). 10 Usability Heuristics for User Interface Design. [ONLINE] Available at: https://www.nngroup.com/articles/ten-usability-heuristics/ . [Accessed 17 February 2019]
Norman, D. A. (1988). The Design of Everyday Things. New York: Doubleday. ISBN: 0-385-26774-6. Call Number: TS171.4 .N67 1990.
Ross, J. (2012). Observing User Research. [ONLINE] Available at: http://www.uxmatters.com/mt/archives/2012/08/observing-user-research.php . [Accessed 17 February 2019].
Summers, B. (2016). How to Make Proto-Personas and Get Everyone on the Same Page. [ONLINE] Available at: http://www.dtelepathy.com/blog/philosophy/how-to-make-proto-pesonas . [Accessed 17 February 2019].
TryMyUI (2016). Quantitative and Qualitative Testing. [ONLINE] Available at: http://www.trymyui.com/quantitative-and-qualitative-testing . [Accessed 17 February 2019].
UTHealth (2016). Provide Informative Feedback. [ONLINE] Available at: https://sbmi.uth.edu/nccd/ehrusability/design/guidelines/Principles/feedback.htm . [Accessed 17 February 2019].
UXM (2010). A step by step guide to scenario mapping. [ONLINE] Available at: http://www.uxforthemasses.com/scenario-mapping/ . [Accessed 17 February 2019].
Veal, R. (2016). How To Conduct User Experience Research Like A Professional. [ONLINE] Available at: http://blog.careerfoundry.com/ux-design/how-to-conduct-user-experience-research-like-a-professional . [Accessed 17 February 2019].
Ward, J. (2010). The Project Management Tree Swing Cartoon, Past and Present. [ONLINE] Available at: http://www.tamingdata.com/2010/07/08/the-project-management-tree-swing-cartoon-past-and-present/ . [Accessed 17 February 2019].
Weinschenk, S. (2011). The ROI of User Experience. [ONLINE] Available at: https://www.youtube.com/watch?v=O94kYyzqvTc#t=11 . [Accessed 17 February 2019].

Web Summit 2018 - My Best of the Rest

Thu, 29 Nov 2018 17:43:17 GMT

Since I put together my previous article, " Web Summit 2018 - My Top 3 Talks ", I have been asked a couple of times about other interesting talks and topics. So I’ve decided to put together two more interesting discussion points that stemmed from talks on the connected world and autonomous transport. All thoughts, views and comments are my own.

Internet / Connectivity

I got talking to a guy in Canada about a phone call he had earlier that day with his nephew. He mentioned to his nephew that he had just come back from a talk by the inventor of the internet. His nephew couldn’t understand what he meant by “the inventor of the internet”. It was impossible for him to imagine a time when the internet did not exist. A time when he wasn’t able to take out his smartphone and WhatsApp his best friend. A time when he did not have access to the world’s information at his fingertips. Thinking about these comments, it’s clear to see how far we’ve come as humans during the last century and how exciting it will be to see how far we can continue to advance with technology over the next 100 years.

Figure 1: Information Source Before the Internet (Trinity College Library, Dublin)

Anyways. Back to Tim Berners-Lee. It was a fantastic moment to see the inventor of the internet speak, or Mr. Internet as I like to call him. THE INVENTOR OF THE INTERNET. Imagine that. One thing I can’t imagine is what it would be like if the internet plug was pulled. Berners-Lee gave an overview of his childhood and it was clear to see that he was destined for a career in computers. His mother was the world’s first freelance programmer and both his parents were part of the programming team that developed the first commercially sold computer in 1951. So his environment was very much focused on the potential of computers, “It was obvious to us growing up how incredibly exciting it was” (The Guardian, 2018).

“All computers are the same, what you do with them is up to you and your imagination” - Tim Berners-Lee

Berners-Lee concluded by putting an emphasis on the importance of teaching kids the possibilities of a career within computers. He recommended that kids should be exposed to a variety of knowledge, skills and beliefs, all of which will be needed as we aim to solve the future of the world’s most challenging problems.

Figure 2: Tim Berners-Lee at Web Summit 2018

Autonomous Vehicles

Imagine the scene, your best friend is getting married. You’ve woke up late and you’re now scrambling to make it to the church on time. Just when you need a bit of luck, there’s no parking spaces in the church car park. You now continue to spend the next 20 minutes looking for the closest space to park. You then scamper across to the church, shielding from the rain as much as possible. Resembling someone who has been dragged through a hedge backwards, you arrive in the back door of the church and make your way inside. It’s too late. Your best friend catches you with a look of disgust. A set of daggers that will stay engrained in your mind for the near future. You are late for the biggest moment of her life. Will she ever forgive you??? Whoa, hang on. Now this is a pretty extreme case. But now imagine, you’ve woke up late. You grab your attire and your toiletries and you head out to your car. You check your social media feed while straightening your dickie bow. The car pulls up outside the church just in time for you to catch the big moment. The car chauffeurs itself back to park snugly in the driveway and awaits your call to pick you up. Wait. What???

Figure 3: Driverless Car of the Future

That’s right, you heard me correctly. The who’s who of everyone is competing to put their stamp on the drive towards an autonomous future. From trains, planes and automobiles, all the major automakers are working on their piece of the autonomous vehicle pie. In September 2017, Volocopter, a German drone firm, staged a test flight in Dubai for what is said to be the first drone taxi service. CEO, Florian Reuter, stated that a user would use their smartphone app and order a Volocopter to the nearest voloport (New York Post, 2017). In July 2018, the Rio Tinto achieved a significant milestone by becoming the first autonomous train to deliver iron ore. Operators more than 1,500 kms away remotely monitored the autonomous train as the 28,000 tonnes of iron ore travelled over 280 kms (Rio Tinto, 2018). In September 2018, Ireland got in on the action by debuting its first fully autonomous bus, which ferried passengers across Dublin’s city centre (Independent, 2018). We are even seeing autonomous vessels making waves in the race to autonomy. Rolls-Royce have partnered with Intel to utilise an intelligent awareness platform and deploy fully autonomous ships by 2025 (The Verge, 2018c). Uber (The Verge, 2018a), Lyft (The Verge, 2018b) and Waymo (The Verge, 2018d) to name but a few are all working to create an autonomous taxi service, and if you look at Tesla, all their cars are being manufactured with sensors that are capable of full autonomy and enough compute power to be safer than a human (Tesla, 2018).

Figure 4: Autonomous Vehicles

Although fully autonomous transport is progressing at a rate that people cannot predict, there’s no denying the apparent ethical implications of safety and job displacement, which is another article in itself. With more than 1.4 billion cars currently on the road (Forbes, 2018) and an estimated 68% of people to be living in major cities by 2050 (United Nation, 2018), the challenges of city traffic life is on the rise. To counteract this issue, it’s estimated that in just two years' time, there will be 10 million self-driving cars on the road (Forbes, 2018). During his talk on smart driving, Jerome Rigaud, COO of Navya, stated that this mobility on demand will combat and solve the traffic challenges of stress, congestion, parking and pollution.

Final Thoughts

We are living in an ever-evolving connected world and technology is advancing at a rate that’s hard to keep up with. We are going to face challenges that arise with the innovations that we create and we are going to continually need the brightest minds to generate ethical solutions that impact humankind for the greater good. We are on the verge of mainstream transport autonomy, but for widespread adoption, people will need to change their mindset, technology will need to advance to a level that ensures passenger safety and regulations will need to be put in place to outline any legal implications that may be incurred. How exciting are these times we are living in? Until next time, I hope you enjoyed the read. GB.

References

Brookings. (2018). Brookings survey finds only 21 percent willing to ride in a self-driving car. [online] Available at: https://www.brookings.edu/blog/techtank/2018/07/23/brookings-survey-finds-only-21-percent-willing-to-ride-in-a-self-driving-car/
Figure Cover: https://echai.in/system/topics/covers/000/000/302/large/WebSummit.jpg
Figure 1: Information Source Before the Internet (Trinity College Library, Dublin). http://wcsa.world/Userfiles/Upload/images/f76b746f06c2356931222de816f32297.jpg
Figure 2: Tim Berners-Lee at Web Summit 2018. http://cdn3.spiegel.de/images/image-1358996-860_poster_16x9-vgzj-1358996.jpg
Figure 3: Driverless Car of the Future. https://3c1703fe8d.site.internapcdn.net/newman/gfx/news/hires/2017/thepromiseof.jpg
Forbes. (2017). 10 Million Self-Driving Cars Will Hit The Road By 2020 -- Here's How To Profit. [online] Available at: https://www.forbes.com/sites/oliviergarret/2017/03/03/10-million-self-driving-cars-will-hit-the-road-by-2020-heres-how-to-profit/#2109434a7e50
Independent. (2018). WATCH: 'This is the future' - Ireland's first driver-less bus debuted in Dublin. [online] Available at: https://www.independent.ie/irish-news/news/watch-this-is-the-future-irelands-first-driverless-bus-debuted-in-dublin-37341362.html
New York Post. (2017). Dubai completes first flying taxi test flight. [online] Available at: https://nypost.com/2017/09/26/dubai-completes-first-flying-taxi-test-flight/
Rio Tinto. (2018). How did the world's biggest robot end up here?. [online] Available at: https://www.riotinto.com/ourcommitment/spotlight-18130_25692.aspx
Tesla. (2018). Full Self-Driving Hardware on All Cars. [online] Available at: https://www.tesla.com/en_IE/autopilot
The Guardian. (2018). Mary Lee Berners-Lee obituary. [online] Available at: https://www.theguardian.com/technology/2018/jan/23/mary-lee-berners-lee-obituary
The Verge. (2018a). Uber seeks permission to resume self-driving car testing on public roads. [online] Available at: https://www.theverge.com/2018/11/2/18056622/uber-self-driving-car-safety-report-testing-pennsylvania
The Verge. (2018b). Lyft unveils a new self-driving car and acquires an AR startup to help it build maps. [online] Available at: https://www.theverge.com/2018/10/23/18014200/lyft-self-driving-car-acquires-blue-vision-lab
The Verge. (2018c). Rolls-Royce is partnering with Intel to make self-driving ships a reality. [online] Available at: https://www.theverge.com/2018/10/15/17979252/self-driving-autonomous-ships-drones-intel-rolls-royce-partnership
The Verge. (2018d). Waymo’s paid driverless taxi service could launch next month, says report. [online] Available at: https://www.theverge.com/2018/11/13/18091024/waymo-commercial-driverless-taxi-service-december-2018-public-launch
United Nations. (2018). 68% of the world population projected to live in urban areas by 2050, says UN. [online] Available at: https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html
YouTube. (2018). Smart driving for smarter cities. [online] Available at: https://www.youtube.com/watch?v=w8EVPBfKQLg

Graham Baitson Blog

Everything is Learnable: Step by Step

Navigate Uncertainty

Be Resourceful

Believe in Yourself

Learn the Fundamentals

Be in the Room

Surround Yourself With Good People

Take Calculated Chances

Leverage Technology

Final Thoughts ﻿

Beyond Buzzwords: One Year Later

The Shift

The Human Layer

Final Thoughts

The Fascination of Language (Part 2: Lost in Translation)

Augenblick (German)

Schmilblick (French)

﻿ Sisu (Finnish)

﻿ Hygge (Danish)

﻿ Final Thoughts

References

The Economics of Flight

A Decade of Delays: Aircraft Manufacturing Challenges ﻿

Supply chain disruptions ﻿

Engine Maintenance and Durability Issues ﻿

Labour Shortages and Production Bottlenecks ﻿

A Golden Age for Lessors

Geopolitical and Economic Challenges

Geopolitical Tensions

Interest Rate Normalisation

Regional Disparities

Sustainability and the Future of Aviation

Sustainable Aviation Fuel (SAF) ﻿

Electric Aircraft

Conclusion ﻿

References

Machines of the Mind: How Artificial Intelligence is Shaping Our World (History of AI)

The Evolution of Revolutions

﻿ 1st Industrial Revolution

2nd Industrial Revolution

3rd Industrial Revolution

4th Industrial Revolution

The Early Days of AI

1950: Alan Turing - “Can Machines Think”

1955: Paving the Way

﻿ 1958: John McCarthy and the Birth of AI

1961: Unimate - The First Industrial Robot ﻿

1966: ELIZA - The First Chatterbot

AI Boom & Winter ﻿

1980-1987: The AI Boom

1987-1993: The AI Winter

Back on Track

Key Milestones

1997: Deep Blue Beats Garry Kasparov

1997: Speech Recognition

2000: Robotic Emotion

﻿ 2003: Robotic Navigation

2006: Personalised AI

2016: AlphaGo Beats Lee Sedol

Conclusion

Hashtags

References

The Future Reframed: From Prompt to Product

Chatting You Up

From Words to Code

How Creative Is It?

How Believable Is It?

What Are the Limitations?

Good Prompt, Great Response

The Business Value

Build or Buy When It Comes To AI

Data-Driven Challenges

Ethical Considerations

Plagiarism

The Future

﻿

From Prompt to Product

Final Comments

Hashtags

Final Thoughts

Sisu (Finnish)

Hygge (Danish)

Final Thoughts

A Decade of Delays: Aircraft Manufacturing Challenges

Supply chain disruptions

Engine Maintenance and Durability Issues

Labour Shortages and Production Bottlenecks

Sustainable Aviation Fuel (SAF)

Conclusion

1st Industrial Revolution

1958: John McCarthy and the Birth of AI

1961: Unimate - The First Industrial Robot

AI Boom & Winter

2003: Robotic Navigation