Insights · May 4th, 2024
In the Spring of 1996 I was sat in the computer lab at Bournemouth University training a single layer Artificial Neural Network (ANN) with grammatical phrases in the hope that I could teach this nascent technology grammar.
It worked 60% of the time, so not with the efficacy that was needed. In my end-of-degree thesis I discussed whether grammar truly existed and the deconstruction of language through slang, cultural movements and a rise in the use of emoticons. Seems highly relevant today as well.
I was excited and bullish on this technology and the application of data-driven decision making and analytics, and I subsequently spent 20+ years at the coal face of this industry – I have the mental scars to show for it. It was rough building data infrastructure, and it still is!
Cut to 2024. The meteoric rise of Artificial Intelligence (A.I.) in the global narrative of industrial progress is impossible to ignore. When I ask the people that come to see my keynotes, “Who here has heard of ChatGPT?” you get 100% response – and that’s from audiences that we can count into the thousands. Many have also used it and some – typically 30% – have used it at work. I am quick to warn folks on implementing technology that produces derivative, and sometimes wholly incorrect, responses into their workflow. Like all new tech, it’s great to play with and dangerous to bet the farm on it.
Many speakers claim to be an ‘AI Expert’, and very few actually are
Easy access to platforms like ChatGPT, Bard, Midjourney, Office 365 Copilot etc. has people exclaiming that the “future of work is AI”, or “it’s not AI that will put you out of work, but someone using AI” delivered with a wry smile and promise that we can prompt ourselves into a new world of opportunity is rife. The acolytes are far and wide and EVERY KEYNOTE SPEAKER I SEE OUT IN THE WORLD THINKS THEY CAN EXPLAIN OUR OPPORTUNITY WITH A.I.
I’ve been studying machine learning techniques and data-driven business intelligence capabilities since the mid-90s. I see very few keynote speakers – my guess is less than 1% – actually talk with experience about how hard this all is ahead of the great leap in progress, and how to do it beyond ‘prompt engineering’. That’s what I have been doing and it’s a more popular opinion than the gung ho let’s go world of kamikaze business strategy – trust and we will fly!
I invite you to test the mettle of any speaker or executive advisor with three (simple) questions to prove actual knowledge of artificial intelligence:
- Explain, in detail and with examples, the process of data creation, collection (across multiple sources), transformation, and preparation;
- Then outline how we can develop, prepare, train and test machine learning models and their efficiency and efficacy against valuable use cases i.e. more revenues, incredible savings;
- Finally, tell us how we can determine trust in the wider organizational and world ecosystem with these A.I. systems available to us to use?
I could do that however, it’s not a keynote – it’s a PhD thesis and would take a long while to prove each part out.
As humans we want shortcuts to the treasure and not the treasure hunt. Therefore, the tsunami of A.I. keynotes we see today from every part of the industry.
Sure, we can immediately see there is opportunity using platforms like these, and we can extoll the virtues of the next hot new thing – remember blockchain and crypto, web3, the metaverse and other hype cycles – however we have to be really careful how we use them and apply what they generate and enable us to do.
We also need to be careful with the warnings we make…
3 Broken A.I. narratives
However, there’s a much bigger problem – broad stroke narratives on what comes next with sober consideration of the reality that these are early and wholly unproven systems
- Millions of jobs will be destroyed – if we encode all information into Large Language Models (LLMs) with infinite tokens and limitless compute and energy then automation totality is assured, and then maybe transcendent Artificial General Intelligence (AGI). The erosion of the blue and white collar workforce is accelerated. I just don’t buy this. One, what I outlined is near impossible due to limits on a number of fronts of compute, data prep and ability to roll out. Second, at no point in the last 300 years through the stages of the Industrial Revolutions have we seen tech introduced and completely destroy jobs per se. Yes, the work landscape changes however, technological advancement actually increases the number of jobs in an economy. What we get is job expansion and an overall betterment of human opportunity (we hope). Of course, we will see worker boss egos still keep the folks pinned down at lower levels than we deserve and get fired “due to A.I.”, that’s another conversation. Your homework is to read about the struggle of Ned Ludd and the reduction of humans to machines (ironic seeing the context of this article).
- The future of [insert industry here] is changed entirely with AI – it’s a tool in the capability stack of an organization, or occupation – not a colonization of that. That’s not saying that people won’t try. They already are and – hoo boy – are they getting the funding to do so. At this stage let’s pour one out for the failed pizza robots and multitude of chatbots and next-level avatars that feel so so natural yet pound us mercilessly into an uncanny valley (I’m looking at you Reid Hoffman). I would say that workplace apathy and laziness may be affected, and not in a good way.
- Everyone is implementing this right now so don’t miss out – in my experience everyone in large organizations has taken a look, is concerned with model poisoning, hallucinations, inaccuracies and increased workload and is investing to establish the foundational capabilities from a tech and change management perspective. In reality, you need to build your own to build trust in your capability – go back elliptically to the three (simple) questions to prove actual knowledge of artificial intelligence.
The biggest problem across all of this – and with any work that drives an organization forward – is ACCOUNTABILITY.
Where does the buck stop with these A.I. systems and how do we entirely explain the structures and learnings – née intelligence – of a model? Right now, we don’t. We’re stuck looking into a mirror where what we see seems off and we just cannot exactly say why. Now we have new processes for checking the quick work we’ve done using generative AI for copyright, lies and formulaic grammar.
Are you ready to take a leap with A.I. having made it this far into the article? Maybe, I can help?
What do we do next?
As a futurist speaker, futures explorer, and hope engineer I am capturing stories relating to the odyssey of A.I. – we already have many – from the defeat of Kasparov and Lee Sedol to the racist chatbots of Microsoft to the algorithmic dogfight prototyped for automated warfare. From a dystopian lens (buy my book – Facing Our Futures) see model poisoning, misinformation factories, and eventual millions in wasted dollars in organizations much like yours.
However it’s not all about failures, or Terminator realities.
In my opinion, the best stories are those small victories of uncovering patterns with real impacts – disease diagnosis, escape path analysis, the slight refining of mission critical widgets. Not sexy to most, but these small steps are incredible to me. They are no frills, manageable and restricted to specific use cases and have followed years of development – something that we can all learn from and aspire to be like within our organizations.
When working with clients and Event Planners I develop custom online guides for clients when I deliver keynotes – here’s one example I wrote for Project Management Institute (PMI) recently – see it here, it’s really quite useful.
I want to be clear – I’m not saying to audiences to not try using A.I. that’s out in the wild. I’m just saying be very careful and seek opinions from those that have been there, are up-to-date with their knowledge, and know from the experience of building and delivering digital transformation.
Reach out, let’s talk about getting people started with exploring our futures with artificial intelligence and so many more signals and trends that will share the dynamics of the 2030s and beyond.
About Nikolas Badminton
Nikolas Badminton is a world-renowned futurist speaker, consultant, award-winning author, media producer, and executive advisor that has spoken to, and worked with, over 400 of the world’s most impactful organizations and governments.
He helps shape the visions that shape impactful organizations, trillion-dollar companies, progressive governments, and 850+ billion dollar investment funds.
Nikolas Badminton’s book Facing Our Futures: How Foresight, Futures Design and Strategy Creates Prosperity and Growth was named Top-50 Business Books of 2023 by The Next Big Idea Club, and selected for 2023 J.P. Morgan Summer Reading List, and featured as the ‘Next Gen Pick’ to inform the next generation of thinkers that lead us into our futures. Reach out to Nikolas to discuss having him come and speak at your event or board retreat – click here.
PS: Nikolas has also been playing with and researching the field of artificial intelligence since 1994. He can tell you and your audience a story, or twelve.
PPS: yes, we used DALL-E for the article image. Bonus point for the reference – contact me if you get it.
