3 x 3! Three AI conferences in 3 Days

What we learnt!

Last week was heavy on AI conferences. On Tuesday we had ‘Think Ahead: The Business Implications of AI’ with the London Business School and on Thursday a double header of The New Scientist’s ‘AI Unleashed - Revolutionising the future of your business’ AND ‘Is AI An Existential Threat to Humanity’ at The Southbank Centre in London. What did we learn?

The Global AI Arms Race & Discontinuous Change

Much was made of the fact that we are now in a “global AI arms race” – which is messy, unpredictable and should be concerning. Where it is going is not clear, but it is outpacing our ability to consider the implications. This picture only becomes more opaque with ‘emergence’ – unexpected AI capabilities that emerge to surprise us.

We have talked before about the future being volatile, uncertain, complex and ambiguous … but following sound scenario planning process there are some clues to the trajectory of this ‘arms race’. The AI revolution feeds off the exponential growth of available data, advances in neural networks and increasing processing power … and these are only going to accelerate:

The Global DataSphere is expected to more than double in size from 2022 to 2026. By 2030 we will have moved from zettabytes of data annually to yottabytes (zettabyte x 1000), and new words have been created for what comes after this[1].

The amount of general computing power in use will increase tenfold, and AI computing power will increase by a factor of 500[2] by the end of the decade.

These increases in available data and processing power will supercharge the development of AI (as if it wasn’t supercharged enough already). What we will experience will be defined by discontinuous change, that is a dramatic change that occurs in a relatively short period of time such that the status quo is suddenly discontinued. And what is likely to catch us out is the speed with which the AI technology will improve i.e. in leaps rather than a gradual evolution. It feels (to carry on with the militaristic metaphors) that as we struggle to understand and manage the impacts of AI, we are likely to be fighting yesterday’s battle.

And yet despite the rather bleak outlook conjured up by the notions of an arms race and disconcerting, discontinuous change, there seems to be plenty of evidence of what we have previously called the ‘hopeful agenda’. One speaker discussing the need to balance opportunity with risk could not envisage anything worse on the utopian to dystopian spectrum than algorithmic bias and election misinformation. Not that the implications of these are not very serious, but there are other big downside risks too. AI brings great opportunities, but we shouldn’t be so complacent about the depth and breadth of the risks. We are not talking here about an existential threat to the human race, BUT there will be clear AI winners and losers.

Levelling Up

Reinforcing what we have read before, there were more indicators of AIs ability to ‘level up’. As a reminder the Stanford/MIT study we have quoted before[3] found that AI is benefiting less experienced and less skilled staff - so they get a boost to their productivity and in parallel it is marginalizing skilled workers who may find that this AI driven ‘levelling up’ is taking away some of their former comparative advantage.

During one conference last week, the panel discussed their findings that ‘winners’ would be organizations that have a more AI friendly structure, background or processes as well as new entrants using AI to push/challenge existing organizations business models (so far, so obvious) – BUT there was some evidence that AI would disproportionately help the worst performing organizations, allowing them to again ‘level up’ with their better performing peers. And beyond the organization, developing countries are looking at AI to level up with the developed world, see technology as “a great balancer”.

What is the difference between those who will readily adopt and those who are more hesitant? It was suggested that at least three factors might stop ‘pockets of brilliance’ becoming ‘a wildfire’, and these are?

• Fear (of scrutiny, of getting it wrong)

• The ‘rules’ (which say you can’t do something in the system)

• Time (time and headspace to make change – understand acceptability of new processes)

Will AI eat our jobs?

The point was made that we are currently figuring out what to do with AI BUT when we start considering what AI can do without us – that’s the more interesting question. We need to find the right balance between what we want humans to do and what we want AI to do/what AI can do – and this balance will be constantly moving and shifting.

It is too early for much ‘hard evidence’ on job displacement but indicators abound.

The CEO of an educational software business who stated in a public forum that ‘in 18-months’ time I will need to employ 20% of the software engineers that I do today, and they won’t need to be college graduates’.

Fairfax Insights review on the impact of AI on the legal profession concludes that “To the extent that more of the routine work, often handled by associates and paralegals, is replaced by AI, there will be an impact on the number of associates and paralegals required […] even if lawyers are still needed to review the output, AI will put a premium on “skilled technology staff” who can get the best out of the tech”. Who would start a job as a paralegal today hoping for a long and satisfying career?

This brings us to one of our favorite anecdotes, which we have seen in print and repeated again last week, and this is that … ‘the factory of the future will have only 2 employees, a man and a ferocious dog. The job of the man is to feed the dog. The job of the dog is to stop the man touching the machines.’

There was also an eye-opening description of AIs ability to reduce “friction” and hence cost. The example given was of the gestation of an advert. Moving from the initial creative to actually filming the ad … you have talent agencies to deal with, actors to book, locations to scout and arrange (and a back-up in case something goes wrong). You have travel, accommodation and restaurants to book. And people to handle all these logistics. You have the process of filming and then post-production.  Lots of people and lots of complication. But AI offers you an opportunity to create the same ad from your laptop – actors and locations are generated by AI. You need none of the expensive logistics. You have none of the friction and hence the cost of actually having to deal with people. People = friction = cost! YOU are friction! It’s this pure substitution of labor by capital – which will lead to tension.

The new world of work

A delegate from OpenAI made the point that routines will be shaken. We still need to figure out how we are going to stand out in this new world of work, and the notion of everything having to fit into the status quo will be problematic. There will be shocks to ‘the system’.

There is a lot of talk connecting ‘how we are going to stand out in this new world of work’ with upskilling or reskilling to meet the challenges ahead. Our point is that we need to engage with precisely/ exactly what this upskilling or reskilling means. Few people are making the point that this is a massive shift in what is required of us humans. It isn’t just about sharpening up thinking skills and being a bit more creative and adding a little bit of edge to what we’re currently doing. We are now staring down the barrel of a fundamental overhaul of what constitutes valuable skills.

We think it is fair to say that none of the conferences we attended last week put enough emphasis on labor market risks – there was (perhaps naturally) a great emphasis on the opportunities and the benefits to organizations but something of an unwillingness to confront the uncomfortable truth that there will be winners and losers – and quite possibly more losers than winners. Should we not be discussing this now?

NB: The Southbank Centre conference (Is AI An Existential Threat to Humanity’) had a slightly different agenda, and we will cover this is a separate note

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[1] Worldwide IDC Global DataSphere Forecast, 2022–2026: Enterprise Organizations Driving Most of the Data Growth, May 2022

[2] https://www-file.huawei.com/-/media/corp2020/pdf/giv/industry-reports/computing_2030_en.pdf

[3] GENERATIVE AI AT WORK Erik Brynjolfsson Danielle Li Lindsey R. Raymond