The author begins the book with a slew of examples involving predictions that never materialized. These examples span a wide range of fields like economics, social sciences, finance, politics, etc. The author also sneaks in examples of his parents and grandparents lives to show how their lives panned out in ways that were completely unpredictable. Well, Do these examples prove anything ? You can quote volumes of predictions going wrong , but if you ask the people who predicted them, they always seem to have a defense. What are the common answers that experts give, when asked about the failed predictions
“Self-negating prophecy” - I predicted the right thing but since there was a massive remediation to the prediction, it never came true ( example – guys who predicted that Y2K would spell disaster)
“Wait and See Twist” – It has not happened as yet but it will soon happen
So, even if one lists down a set of predictions that went wrong , it is rather difficult to actually rigorously state that the prediction went wrong. Again whoever quotes a set of predictions going wrong is accused of cherry picking specific predictions. What’s needed is the ”rate of failure" to understand whether expert predictions work ? But to compute the rate of failure, we need hits too . How do you identify hits ? What if the an expert has a poor failure rate but hits bulls eye for the event that we picked ? How does one identify a dart thrower Vs an expert giving right prediction ? So, even though it is easy to identify certain specific instances where predictions have gone wrong , if we take logic and evidence in to consideration, "figuring out how experts are at predicting future" is a challenging question. One might have to dedicate one’s whole life to carry on such an experiment and see what results it throws up. One man has done this feat. Philip Tetlock, a professor at Haas School has conducted one such experiment spanning over 2 decades collating about 27,450 predictions and their outcomes by interviewing and collecting prediction statements from a diverse set of experts in various fields. It is possibly one of the most scientific experiments conducted to answer the question of expert’s rate of failure. The result of Tetlock’s experiment was that expert guesses were as good as random guesses,i.e a dart throwing monkey. He also noticed two other things. There were experts who did pathetic as compared to coin toss. The other interesting thing that he noticed was the experts who had a lower rate of failure in their predictions has one thing in common. They had a different style of thinking.
This meant that they had no prior template to fit the world events. They were self-critical about their own opinions as well as others. Basically they predicted with a healthy dose of skepticism towards any predictions. This book basically tries to discuss this specific style of thinking using the analogy of Hedgehog Vs Fox.The sum and substance of Tetlock’s study was " Foxes beat Hedgehogs".
The author says that predictions work extremely well when the system governing the response variable and its predictors follow a linear model. The planetary system, occurrence of tides, etc. are all systems that are linear in nature, i.e the equation is in some linear form and can be estimated with surprising accuracy. So ,we are in position to exactly say the time for a solar eclipse at a certain location on earth but are terribly poor at predicting events like demographic, political and social events. Why? The entire system is non-linear and feedback dependent. Slight changes to the input data creates a great model uncertainty. The author makes a strong argument against modeling any non-linear system, i.e pretty much every forecast that we see in the media.
This chapter concentrates on two areas of predictions,demographic predictions and oil price predictions. Through a series of predictions , a case is made that non-linear systems are dependent on "monkey bite" moments, a phrase that means that trivial events can have unimaginable consequences. Well the actual phrase was used by Winston Churchill when he wrote that a money-bite caused a war between Greece and Turkey. Its the butterfly effect. The chapter ends with a clear message , i.e price of oil is fundamentally unpredictable and so are demographic trends. However both the fields employ tons of experts to dish out opinions and report. Why ? Answer is simple : There is a demand for forecasts , i.e. ‘Seer – Sucker theory'(No matter how much evidence exists that seers do not exist, suckers will pay for the existence of seers).
This chapter talks about human brain and why it is hardwired in a way to see patterns when they aren’t. It cites an example of Arnold Tonybee , an expert who became insanely famous predicting stuff and was subsequently criticized by many when his predictions failed to materialize. Centuries of human brain development has equipped to see patterns when there are. Failing to spot real patterns is a matter of life and death. However evolution has not put a penalty or hardwired the brain in the case of Type II error, seeing a pattern when there isn’t. So, basically human brain does not have intuitive sense of randomness. Hence we come across people who keep on predicting stuff despite knowing that the underlying process is random.
What about experts ? What’s going on in the mind of experts ? The author uses Philip Tetlock’s conclusion that Experts in a specific field had a greater rate of failure than people outside the field,i.e hedgehogs fare badly as compared to foxes. As the saying goes, "Theory is the root of all Evil", hedgehogs are blinded by confirmation bias. As they amass more and more knowledge, they are blinded by their own subconscious beliefs and start picking and selecting information that suits their overall theory. In a classic book on Volatility by Ricardo Rebonato, I came across a similar analogy. Option valuation can be done in two ways, one an option-replication argument (the "hedgehog approach") , the second is a "fox approach" where you don’t stick to one theory and incorporate a healthy dose of randomness in valuing and trading of options. People who stick to option-replication argument are typically seen in academia spinning yarns(theories), all basically resting on this one hedgehog theory of option-replication. In fact Taleb in one of his books says that pricing and trading anything beyond plain vanilla European options is very complicated and error prone and any amount of math cannot come to our rescue.
The takeaway from this chapter is that Foxes are right about a lot of things. Hedgehogs are mostly wrong. They are deluded despite their brilliance.In fact they are deluded because of their brilliance
Books like these made me wonder," Whether there is money to be made in long only investing?" As they say , Stocks Are Stories, Bonds Are Mathematics. In my work environment, I see people around me who have invested their lives in stories(stocks) and have chosen "long only stock picking" as a career. They religiously weave stories in their minds by following stock specific information and talk about them with their tribe. With an increasingly non-linear world around, where "monkey-bite" moments have far reaching consequences and where info overload is leading to more and more confirmation-bias, it looks like hedgehogs are going to lose out to foxes.
This chapter talks about findings from behavioral economics and gives examples of status quo bias, anchoring-and-adjustment bias, availability heuristic, representative heuristic. The rationale behind mentioning these biases is that author wants to make a point that neither hedgehogs nor foxes are good at getting over these biases always. He also debunks `scenario-planning’ as another bogus exercise and if facts are to be taken at face values, umpteen scenario analysis sessions at various MNCs and other firms around the world , hardly have given rise to any meaningful correct predictions. The problem with scenario planning as explained in this chapter is that, foxes tend to run to the other extreme of hedgehog’s stance. It is mainly to draw attention to the people who are carried away from status-quo bias. However by going to other extreme, they are often blinded by representative bias.
This section mentions that everyone one of us is unsettled by uncertainty and it is hard to live and accept uncertainty. Hence the craving for experts and their predictions. Also for a guy who is already hedgehog for a certain number of years, it is difficult to crossover and become a fox as he/she senses a financial and psychological cost to it. I came to know from this book that Robert Schiller who is known to have predicted real estate crisis hardly did any thing in the meetings and committees that he was part of. In his own words, there was a great disincentive if he would have voiced his opinions more aggressively. Basically that means he was trying to fit in and align with his personal incentives. Nothing wrong with it. May be that the way world is. The point to be noted is , status-quo bias is tough to fight.
The content in this chapter revolves around this behavior of most of us – ‘We tend to forget misses and focus on hits’. All the experts who have failed in predictions are forgiven easily.The TV channels, the columnists, and many more people do not criticize them. However they latch on to their hits and do not even mention their past failures in prediction. Its like
This coupled with hedgehogs who exhibit oodles of confidence in their predictions makes us all suckers for their statements.We give in. The chapter is interesting as it cites many examples like Peter Schiff, Robert Shiller( who were hailed as people who predicted crisis correctly) and shows that in each of the cases, they really did not make the prediction in the way media has projected it. In a way, it seems to say that we are suckers for certainty and there are hedgehogs who basically deliver it. Looks like a perfect demand supply equation. Who cares whether the predictions went right or wrong.. May be the poor investor in the fund whose manager made a call after listening to hedgehogs.
This chapter talks about the cognitive dissonance and its role in experts life or a hedgehogs life. Cognitive dissonance , in modern psychology, means rationalizing the events to suit one’s philosophy and thinking. When hedgehogs find that their predictions have not come true, cognitive dissonance comes in to play and then they rationalize their failure at prediction. Two most common ways to duck their failure is 1) time is still ticking, they got it wrong on the time scale. 2) they misremember things to suit their needs (hindsight bias). The author cites a few examples of cognitive dissonance in play. He goes on to say that not only hedgehogs but also the fans of hedgehogs can undergo cognitive dissonance and they conveniently misremember stuff.
Meta cognition: Constantly think about how you think
Humility: Have a healthy dose of skepticism about any forecast that you make. In-case any of your forecasts is a hit, be humble to accept that chance played a role ( George Soros constantly does that)
The book is an accessible introduction to Philip Tetlock’s research. The author puts a spin on one of the Tetlock’s conclusion, i.e there are two types of experts, Hedgehogs and Foxes. Hedgehogs believe in one big theory whereas Foxes have a more elastic kind of thinking. The takeaway from this book is that developing a Fox style of thinking is a better alternative in this non-linear unpredictable world. The book does not criticize experts(Hedgehogs) but gives an explanation about a) why they dish out opinions with such certainty? and b) Why do we constantly seek out for such experts ? After reading this book, I guess it will make make any reader take "predictions" with a healthy dose of skepticism, if he/she is not already doing so.