📚 On regression to the mean in Fooled by Randomness. Beware the uncontrolled phase 2 data, especially ones with surprisingly large effect sizes.

📚 Halfway through Fooled by Randomness, the seeds of Antifragile. It’s all one work, all that’s missing is cross-references from earlier to latter written parts.

📚 Catching up with John, the busted high-yield trader in Fooled by Randomness.

If you are talking about a 10 sigma event you should have thought in alphas, not sigmas. There may be early hints that the data is not Gaussian but people call them outliers and brush them away.

📚 Fooled by hindsight bias. This one is for anyone who thinks lockdowns and school closures in the spring of 2020 were a mistake.

Making ex post “predictions” is infinitely easier than ex ante, and gives you a false sense of confidence to boot. Dangerous and stupid.

📚 Taleb the prophet, writing about cryptobros and the summer of 2022 back in the early 2000s.

Financial instruments come and go but human stupidity and greed are forever.

📚 Re-reading Taleb’s Fooled by Randomness for the first time since covid hit. From the preface, on intellectual immodesty. There is a direct line from this to the catastrophic early response to the pandemic.

BTW, our company is called Cartesian but we are Montaignes at heart.

📚 Calculated Risks was funnier than you’d expect from a book about statistical (in)numeracy. It’s healthy to laugh in the face of our inadequacies.

To get yourself in the right frame of mind before reading this book, try watching a few optical illusion videos. There is no reason to think our visual cortex is any dumber than the rest of the brain — in fact, quite the opposite. That our inference can be so easily fooled in a domain which is supposedly our strong suit is humbling.

Our statistical inference is even worse, so a short book or two on statistical numeracy should be in everyone’s library. Gerd Gigerenzer’s Calculated Risks can be that book for most people. The assumption, easily defensible, is that “most people” will get more use out of understanding frequentist rather than Bayesian probability. After all, most probabilities people are bombarded with — your chance of dying from breast cancer with and without screening, the chance of your neighbor being the killer given a positive DNA match (you know, the day-to-day stuff) — is frequentist.¹

The only reservation to wholeheartedly recommending Calculated Risks to everyone is that it falls into the category of “blog post books”, if you believe that most non-fiction books should, in fact, have been just blog posts. Or, since blogs are out of vogue, a 15-minute YouTube video may do. Or perhaps a single sentence: use natural instead of relative frequencies (e.g. 1 in 10.000 instead of 0.01%). Let your faulty cortex fill in the rest.

📚 Bullshit Jobs ended up being copy pasta of David Graeber’s fan mail. Too bad, as the premise is as relevant as ever.

A massively biased and, ultimately, underwhelming account of jobs that even people performing them think shouldn’t exist. It is biased because David Graeber’s sole source of information — beside his own flowering mind — were his Twitter followers. More precisely: his followers' self-imolations in prose sparked by the short essay which popularized the term. So you get not only a self-selected sample of young middle-class professionals discontent with their jobs, but also the attempts of that sample to connect with their anarchist idol. A fun game to play while plodding through these accounts — accounts which, by the way, take a full half of the book — is to spot the embelishments. There are many, and some even Graeber marks as such.

As for underwhelming, well, the book’s purely descriptive nature wouldn’t be so bad if it weren’t skin-deep. Graeber comes frustratingly close to asking some interesting questions; ⊕ In no particular order: Should we be worried about AI taking our livelihoods if most jobs are irrelevant anyway? How much of what doctors do is bullshit, and are they aware of it? Is the private sector just as bad as the government in real-to-bullshit job ratio, or are some companies better than others, and is that reflected in their market value? Are there any signs of de-bullshitization in countries that experimented with Universal Basic Income? alas, that would have required too much research. Instead we got fan mail copypasta and cheap digs at the corporate culture. So it goes…