Contents

  1. Predictably Irrational (2008) by Dan Ariely
  2. Thinking, Fast and Slow (2011) by Daniel Kahneman
  3. Antifragile (2012) by Nassim Nicholas Taleb
  4. The Signal and the Noise (2012) by Nate Silver
  5. Stumbling on Happiness (2005) by Daniel Gilbert

I prefer to stay away from book reviews, just not my thing. I learnt long ago that people review a book by trying to answer the wrong question: why should anyone buy this book? But the instructive question is why should anyone read this book? Even though I’ve bought (and continue to buy) lots of books, I only care about the second question. Needless to say that I’ve read far more books than I’ve bought. My justification for buying any given book is always convenience, which is totally unrelated to my justification(s) for reading that book.

However, that being said, it’s definitely useful to review my canon of uncertainty for the sake of posterity. These are the books that have moulded my thinking about uncertainty, risk, and decision making. I find them immensely enlightening, and would strongly recommend them to everyone for reading. Below are my brief remarks for each book, presented in the order that I read them (but note that the copyright year listed in each citation is for reference only).

Predictably Irrational (2008) by Dan Ariely

I read this book in late 2009. I initially saw Ariely’s TED talk on YouTube, then borrowed the book from a library, and eventually bought it for convenience. It introduced me to psychology research and behavioural economics. Ariely wrote about all sorts of cognitive biases that made a mockery of the economic orthodoxy concerning human rationality. The spooky thing was that I recognised pretty much all the biases in myself. So it was a revelation about how I tended to be mistaken whenever making decisions in a hurry. It made me question the value of intuition, and I started to distrust my intuitions about most things. This book was also the first time that I came across the work of Amos Tversky and Daniel Kahneman.

Thinking, Fast and Slow (2011) by Daniel Kahneman

I read this book in early 2012. I bought it straight away for reading, because I was already convinced about the truth in Kahneman’s research. This is an absolutely astounding book. It fleshed out all the ideas that I had begun to comprehend from psychology research. It changed my daily vocabulary, as Kahneman overtly intended in the book. I now routinely try to rein in my System 1 and give more time to my System 2 when faced with judgement under uncertainty. Even though Kahneman said he’s pessimistic about anyone being able to improve their thinking after understanding his research, I find it very useful just being aware of the cognitive biases that he and Tversky uncovered. It’s a matter of discovering my ignorance in spite of often failing to cure that ignorance.

Antifragile (2012) by Nassim Nicholas Taleb

This was the first book of Taleb that I read in late 2013. I immediately proceeded to read all his other books up to that point (especially The Black Swan). I’ve found his conception of antifragility as limited loss plus unlimited gain to be the most insightful way of tackling uncertainty and risk. It helps me pick the right option when faced with a dizzying array of choices. It also eliminates a great deal of ex post facto regret due to the hindsight bias. Taleb’s expositions of fat-tail and multi-fractal statistics are second to none. His mathematical papers are excellent supplement to his books. He has an aphoristic writing style that lends itself to memorable one liners everywhere. Indeed, his short book The Bed of Procrustes is an entertaining collection of original aphorisms.

The Signal and the Noise (2012) by Nate Silver

This is the best non-technical book I’ve read (first in late 2013) about Bayesian statistics and probabilistic thinking. Silver discussed numerous domains of forecasting, some accurate and some hopeless. His main conclusion was to imagine multiple possibilities first, then apply Bayesian techniques to estimate a posterior probability distribution. So instead of predicting a narrow range of possibilities, it’s far better to focus on as broad a range as possible while always remembering that any associated probability is never certain (i.e., never 0 and never 1, but something in between). A key lesson I learnt from this book is the remarkable value of Monte-Carlo Simulation, which is a powerful tool for grappling with complex uncertainties in life.

Stumbling on Happiness (2005) by Daniel Gilbert

I read this book in late 2017, but I wish I had read it much earlier. In any case, it answered a bunch of important questions that I had about imagination and memory. Gilbert explained brilliantly how our imagination systematically failed, and how our memory was flawed as well. The two of them typically combine to create a pernicious situation where we become convinced about our future happiness, only to be disappointed when the time comes. His sense of humour shone brightly, and the book was a pure joy to read. I now have a deep curiosity to study Gilbert’s research, because it is intensely illuminating.