In his explanation of Bayes' theorem, cognitive psychologist Steven Pinker highlights how this type of reasoning can help us determine the degree of belief we assign to a claim based on available evidence.

Bayes' theorem takes into account the prior probability of a claim, the likelihood of the evidence given the claim is true, and the commonness of the evidence regardless of the claim's truth.

While Bayes' theorem can be useful for making statistical predictions, Pinker cautions that it may not always be appropriate in situations where fairness and other moral considerations are important. Therefore, it's crucial to consider when Bayes' theorem is applicable and when it's not.

0:00 What is Bayesian thinking?

1:01 The formula

2:41 When Bayes’ theorem obscures the solution

4:25 Bayes’ theorem in a nutshell

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About Steven Pinker:

Steven Pinker is an experimental psychologist who conducts research in visual cognition, psycholinguistics, and social relations. He grew up in Montreal and earned his BA from McGill and his PhD from Harvard. Currently Johnstone Professor of Psychology at Harvard, he has also taught at Stanford and MIT. He has won numerous prizes for his research, his teaching, and his nine books, including The Language Instinct, How the Mind Works, The Blank Slate, The Better Angels of Our Nature, The Sense of Style, and Enlightenment Now: The Case for Reason, Science, Humanism, and Progress.

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