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The formula for rational thinking explained by Harvard professor Steven Pinker.
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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
Read the video transcript ► https://bigthink.com/series/explain-it-like-im-smart/bayes-rule
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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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Read more of our stories on rationality:
Bayesian search: A simple rule to find stuff you’ve lost
► https://bigthink.com/smart-skills/bayesian-search-find-stuff-lost/
Hasty generalization: how to escape your biases and be more rational
► https://bigthink.com/thinking/hasty-generalization-bias-rational/
System 1 vs. System 2 thinking: Why it isn’t strategic to always be rational
► https://bigthink.com/the-well/system-1-2-thinking-fast-slow/
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Source
What's an example of you can apply Bayes' Theorem?
Lovely video, thank you.
Noise playing while he’s speaking, is unnecessary, distracting and bloody annoying!
Pinker and Epstein.
Yeh 'kehna kya chahte' hai!!🤕🤔🥱
I don't understand why YouTubers think adding music adds anything; it doesn't. I tried to hear Dr. Pinker's words, but the music was so distracting, I had to quit.
priors – centuries ago 99% of people accepted that earth was at the center of the universe
This was a weirdly explained tangent.
This has nothing to do with right or wrong. That is a problem.
Isn't this Confirmation Bias though?
How not to learn something…. put knowledge mixed in with music …. Are you trying to degrade society and knowledge because i am struggling to learn. I was going to say at the beginning it's ripped off because of all the crappy music, but the author looks reasonable…why the music
"If you could follow what I just said, (Mumble, mumble, mumble)" What? I could maybe follow what you just said if I listened to it again a bit at a time without the very distracting images and music, but what you said at the end remains a mystery.
so… do you have to make sure that the "prior" doesnt include any cases where the new evidence is included in the outcome?
If so, it seems like there needs to be a critical look at the "prior" so that its not skewed by containing what you think is "new evidence".
Not a licid explanation at all.
First thing people have to understand is probability is not an intuitive topic to be expert at. It needs sleepless hours to look at the same problem from various perspectives, lot of experiments and invalidating your own theory and what not .Bayes' theorem is nothing different let alone Markov's chain.
Bayes’ theorem doesn’t actually “fail” here — the model does. Specifically, in the part about inferring someone’s long-term trajectory from adolescent school performance, the theorem just updates whatever priors/evidence you feed it. If the inputs are oversimplified — e.g., treating grades as a proxy for ability while ignoring other facets like ADHD, boredom, late maturation, system-fit, etc. —the posterior will be wrong. That’s not a limitation of Bayes; it’s garbage in, garbage out. The problem is epistemic, not mathematical: an incomplete map of reality, not a broken theorem.
Pinker is a treasure of humanity. I have read and reread many if not all of his books. Among the 800 or so books on science, philosophy, self-improvement, and being a decent human I’ve been privileged to read, Pinker stands among the best by the metrics that matter.
One of the most important Pinkers of our generation!
Personally, I don't have much Trust in the 3 Macro Theories (Big Bang, General Relativity's Fabric of the Universe and Evolution Theory) because I always said it too soon to come to any conclusion. Modern Science is just too New (400 years) to gather all the information required to come to any conclusion. I however believe that Statistics could help in this regard. Something like BAYES Theorem should LEAD the way to define as how we should really see the Evidence.
I use bayes theorem to win that blackjack on Golden Palace when that was a thing and I could have a piece of paper in front of me counting cards. I took them for $5500. I also use it to make myself a bit of chess player, and also in a multitude of other ways
They said she would rather suck your dick than mine every night before she goes to bed she would rather suck your dick rather than mine before she goes to bed do you understand the implications of this😂😂😂