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Rationality & Bayesian Thinking Bayes' rule as a habit rather than a formula: priors, strength of evidence, conservation of expected evidence, beliefs that pay rent, reference class forecasting, when expected value breaks, the value of finding out, and how to disagree so that someone changes their mind.
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Reading list The works this deck draws on, in the order worth reading them. Cards point to a specific chapter or paper where one fits.
01 Book Rationality: From AI to Zombies · Eliezer Yudkowsky The source of most of this deck's vocabulary (paying rent, conservation of expected evidence, privileging the hypothesis, noticing confusion). It is very long; read the sequences Map and Territory and How to Actually Change Your Mind and skip the rest. 02 Book Superforecasting · Philip Tetlock and Dan Gardner For this deck, the chapters on how forecasters break a question into pieces (Fermi-style), start from the outside view, and only then adjust with the inside view. 03 Book How to Measure Anything · Douglas Hubbard The clearest practical treatment of the value of information: why most measurements people pay for were not worth it, and how to find the few that are. 04 Book Thinking in Bets · Annie Duke Read it here for the wanna-bet move: how treating a belief as a wager you might lose changes how carefully you hold it. 05 Book How Big Things Get Done · Bent Flyvbjerg and Dan Gardner Reference class forecasting from the person who built the method, with the data on why projects of every kind run over and the few that did not. 06 Book Algorithms to Live By · Brian Christian and Tom Griffiths The chapter on Bayes' rule is the best short explanation of priors in everyday prediction, and the optimal stopping chapter is the mathematics behind knowing when to stop looking. 07 Book The Scout Mindset · Julia Galef Already the starting point for the metacognition deck; for this one, read the chapters on holding your identity lightly and on changing your mind in small steps. 08 Book Probability Theory: The Logic of Science · E. T. Jaynes The hard, foundational book: probability as extended logic, built from first principles. Only for someone who wants the mathematics; the first two chapters repay the effort even if you stop there. 