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Bookshelf (and why would you want to read any of this?)

This is intentionally a long, unorganized page, instead of a database. I’m sure you have seen databases of book recommendations and you don’t need another one!

The only way to get better at forecasting is to learn how to calibrate your probabilities.

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What could go wrong with forecasts, and how can we get better at it? Who would have thought: by practicing it! Well, I didn’t think of that until I read the book.

Although Tetlock’s second book, Superforecasting is probably better, it doesn’t have long description of how forecasts that seemed to be wrong at the time of writing were misguided (like, Russia invading Ukraine). Forecasts, that later, in the 2020s became reality. This really brings an entertaining light on how fragile our predictions are, how much timing luck is involved, and how easily we can fool ourselves with rationalization.

Aside of that, the book is fundamentally about the practices that makes us better forecasters - probably the most useful meta-skill in life?

Don’t assume all distributions in real world are Gaussian, or that you can transform them to Gaussian that easily.

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Wonderland by Steven Johnson

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Creativity code - Marcus du Satoy

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The Information - James Gleick

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