“People calculate too much and think too little” – Charlie Munger
It was in 1987 that Economist Robert Solow said, “You can see the computer age everywhere but in the productivity statistics”, and the comment appears as relevant now as it was then. Whilst credible explanations for this “paradox” have been put forward, developed countries continue to suffer stagnant economic growth that is blamed, amongst other things, on stalled productivity improvements.
Whilst the prospect of “AI powered everything” holds the promise of us both working less and achieving more, the ever-higher expectations being placed on AI increase the risk of disappointment [1]. This is an issue of importance to investors, because of the impact it might have on their jobs, and the broader impact on the economy. Are we on the cusp of a productivity driven boom or is technology placing a squeeze on most people’s disposable incomes that is holding back growth?
I came across Munger’s quote last month in the writings of a highly respected value manager, and it resonated with me. It resonated because I see the current enthusiasm for AI as further devaluing the importance of human thought. Although the current crop of “generative AI” models present human-like abilities to create text, images or videos, it would be a mistake to believe that they possess an ability to think. They do not. They are trained on unimaginably huge quantities of data that they “slice and dice” to create their impressive results.
With a background in statistics and computing I am a believer in both the power of using data to make decisions and the benefits of automation. Despite this I think the importance placed on “thinking” has been reduced in our industry, as it has in other aspects of our lives.
Much more energy is expended by the investment industry on modelling next year’s earnings, than it is on contemplating the longer-term challenges or growth drivers for a company. I think that this is in part because humans seek comfort in the certainty of exact answers, even if they are answering the wrong questions.
Deeper trains of thought allow you to engage in “second level thinking”, exploring the knock-on effects of the obvious. It helps you see what others don’t. In a world that is becoming increasingly flooded with information, I see an ability to make sense of it as even more important. Whilst automation frees up time for thinking, it does not remove the need for it.
The market environment since the financial crisis in 2008 has favoured large companies, favoured US listed companies, and seen the risk of falling share prices underwritten by government. This is an environment where investors did not need to think to do well, as it is an environment that favoured investing in passive indices over actively managed funds.
I cannot know if the market environment is shifting in favour of active management, but it would be a mistake to think that the large companies which dominate the passive indices must always out-perform the smaller ones that active managers generally favour. Likewise, it would be a mistake to think that the risks of financial loss in investing will always be “socialised”.
The punch line that we “like to think” is, at first sight, underwhelming. Apologies if you were hoping for something deeper! However, I see the world shifting in a direction where it is becoming a rarefied skill, and one that investors should value.
[1] Emily Bender and Alex Hanna’s book on this subject makes for excellent reading (THE AI CON – How to Fight Big Tech’s Hype and Create the Future We Want)