DEATH OF A GURU: A FAN’S TRIBUTE TO NOBEL-WINNING LITERARY ICON KAHNEMAN
Sad to hear about the demise of my favourite author, Daniel Kahneman—the closest thing I have had to a Pin-up! Both his books, Thinking Fast And Slow, and Noise, that he co-wrote, are among my top five of all time.
Nobel Laureate. Best-selling author. Psychologist who never taught an economics class, but had a tremendous impact on the study of economics and finance. That’s not all. His influence was far wider, in fields ranging from sports to organ donation.
There have been obituaries from people who knew him and worked with him. But this is a fan’s tribute.
His writings introduced me to new worlds.
His work was about fallacies in human thinking and judgement. And that covers just about every area of human endeavour. It is nearly impossible to summarize even a few points from his work in this piece.
The short point: we are far less rational than we think we are. Human evolution has ensured that our brains are wired for efficiency in survival, not necessarily for truth and rationality. We take many sub-conscious short-cuts to reduce cognitive load, and end up thinking ‘fast’, using System 1, as Kahneman calls it, most of the time. Thinking ‘slow’ when we look at data, and analyzing it properly before coming to conclusions is done, but rarely.
This results in many systematic biases. For example, once an incident has happened, or known—say, a poll result—we tell ourselves that we always knew how this would turn out. This is hindsight bias.
Most of us think that we are above average in almost every field, which is a statistical impossibility. This is why we refuse to look at, or ignore, statistical probability or averages, when undertaking any new venture. Explains why, however many times the Securities and Exchange Board of India (Sebi) points out that less than 10% of options and derivative traders make any money at all, there are enough people jumping in, thinking they will defy the odds.
He also writes about how anything that dominates the media will become more salient in people’s minds. The human mind cannot distinguish between familiarity and truth. Lies repeated multiple times will start to appear true.
There are dozens of other biases he explains: Survivorship bias, where we remember only the successes, for example, stocks that have done well, and forget the rest; Sunk cost fallacy, where we invest more time and money on anything from a business to a relationship, simply because we have invested in the past; Halo effect, Anchoring effect, Framing fallacies and many more.
It is fascinating to learn about these biases. But, as Kahneman himself warned in several interviews and in his books, intellectually understanding them does little to change how we really operate in the world. He said that in spite of a lifetime’s work in this area, his own decision-making had barely changed, and he continued to make the same mistakes as everyone else.
The reason is that many of these thinking fallacies are hardwired into our brain because they served a purpose during human evolution. In our hunter-gatherer days, if there was something that looked like a sabre-toothed tiger in the bushes, it was better to take pre-emptive action even if it later turned out that there was no tiger there.
In today’s world, it translates into tendencies such as the reluctance to book losses in the market.
What I love about his books is that each chapter has as much substance as most other non-fiction books. The latter often have just a few ideas stretched out to book length.
While Thinking Fast And Slow speaks about systemic biases, Noise, which he co-wrote with Cass R. Sunstein and Olivier Sibony, is about the random element in human decision-making. One key takeaway: a well designed algorithm, or rule-based system, will almost always beat a so-called experienced expert in any area of human enterprise that requires judgement.
The reason is simple—human beings are prone not just to biases, but also to noise.
Equally experienced experts in areas like judicial sentencing, insurance or investing, will differ dramatically in making a judgement on the same issue, and with the same facts or information.
This variability is noise, which can be reduced by having a proper system.
You can easily visualize this: give the same company information to an array of stock market experts, analysts, or fund managers, and each will have their own take on it.
That, in short, is noise.
In a sense, this book is an endorsement of the path which we chose at First Global to put all our years of research expertise into an artificial intelligence and machine learning system, which could then be applied on a bias-free, noise-free basis across the whole universe of stocks.
A few other fascinating tidbits For example, we have all the Nifty forecasts for end-2024 from every stock market expert and securities house.
The truth? It’s in a category called ‘objective ignorance’ in the book. Nifty predictions are only one example of humans forecasting things which cannot be known—that too with huge conviction and confidence.
If systems work better, why don’t we outsource many such functions to machine- or computer-led systems? The anomaly lies in how we judge the competing systems. We intuitively know that human beings will make errors, but consciously or not, expect a machine-led system to be totally error-free.
I could go on…
As I said, this is at best, a small glimpse of Kahneman’s work, but the windows it unlocked in our minds will hopefully remain open. Rest in peace, my last Guru.
(Devina Mehra is the founder, chairperson and managing director of First Global, an Indian and global asset management company)
His work was about fallacies in human thinking and judgement