I want to get rich, powerful and famous so I have changed the name of The Levelling to ‘The LevAIlling’, to reflect the growing mania around the deployment and power of artificial intelligence (AI). Readers can rest assured however that all the output on these pages is organic (I had tried ChatGPT a few months ago but was not impressed).
AI has been around for a while, as have its many dangers. In ‘The Levelling’ we wrote about how algorithms were both causing and provoking inequalities and social injustice. Last summer we flagged the very sinister example of how the Spiez Laboratory in Switzerland (see the Final Problem) one of whose specialisations is the study of deadly toxins and infectious diseases (located not too far away from the Reichenbach Falls), where scientists performed an experiment where they deployed an AI driven drug discovery platform called MegaSyn to investigate how it might perform if it were untethered from its usual parameters.
In short, MegaSyn produced nearly 40,000 designs of potentially lethal bioweapon standard combinations (some as deadly as VX). It is an excellent example of machines, unconstrained by morality (humans have willingly crossed this moral threshold), producing very negative outcomes. In another recent note ‘Talos’ we explored some of the emerging philosophical issues around AI.
Two aspects of the AI story that we have not yet mentioned are the stock market and the labour market, both of which will be greatly impacted by AI.
A sure sign that AI has arrived is that it is creating a stock market bubble. Since the start of the year, ten companies have driven the performance of the S&P 500 index, nearly all of whom have some form of AI business.
In particular, Nvidia which seems to have been at the centre of multiple market bubbles (bitcoin, gaming, semis) is the lead play in the AI investment trend. From a valuation point of view the price of the company’s stock trades at 30 times the value of its sales (for normal businesses 3 times is quite pricey), which is not far off the valuation levels that have marked the top of ‘fads’ or bubbles. What we do not yet have is a broad AI bubble in the sense that even companies with a passing association to AI and its necessary infrastructure trade at bubble valuations. Similarly, markets have not priced in the intensity of competition between the big AI centric technology firms (Microsoft versus Google), not the disruptive threats they face from open source AI projects.
Much the same is true in the venture capital world, where AI funds and companies are one of the few ‘hot’ areas in VC. The popular ‘discovery’ of AI by the media is having a sizeable impact on the VC world in terms of providing the catalyst for funds to deploy cash to AI centric projects. Notably a whole range of companies is now touting their AI credentials, and slipping the AI moniker into their business description, in the same way that in 1999 companies adding a ‘dot.com’ surged in value.
In addition, companies reporting earnings, discussing their earnings on conference calls or even those appearing on financial TV (i.e. CNBC) will slip the phrase ‘AI’ into their dialogue so that this is picked up by AI driven analytics that in turn feed into stock buying programs.
If one popular reaction to a new innovation is that it will drive an investment bubble, then another is that it will fatally disrupt the ‘old world’, in the way that bitcoin was supposed to supplant the dollar and euro. In the case of AI, the promise is that it will cost us our jobs.
Labour markets have already been softened up in the past five years from ‘stay at home’ to the ‘great resignation’ to the ‘digital economy’, and they (in the G7) have arguably never been as robust. While there are some fields that are being disrupted by AI (the EU no longer needs 17% of its translators apparently) the best examples I have come across are where high performing humans – from surgeons to soldiers – use robots and artificial intelligence to do their jobs better.
While there is now a growing consulting trade on the future of the labour market (the WEF Future of the Jobs market 2023 report is a good starting point). One of the areas that is missed by many such studies are emerging market workforces -where regulation, social welfare and training levels are not at all as developed as they are in Europe for instance.
In some of the large emerging nations like India, training and education can be formulaic (I am not a fan of Byju as a firm) and could well expose knowledge workers in those countries to disruption by artificial intelligence. I belief that this is the great faultline of AI as it concerns labour, because if the effect of artificial intelligence on work is as great as many say, it could slow the natural path towards productivity and higher incomes of many emerging nations, the vast majority of whom do not have the industrial/capital base or expertise to build their own AI platforms (as Google is doing).
As it stands, there is also very little policy coordination between emerging nations, which again leaves them vulnerable in the face of AI. AI versus EM might become one of the great contests of the 21st century.
Have a great week ahead,