TLDR: It's often said that Bayesian updating is unbiased and converges to the truth—and, therefore, that biases must emerge from non-Bayesian sources. That's not quite right. The convergence results require updating on your total evidence—but for agents at all like us, that's impossible—instead, we must selectively attend to certain questions, ignoring others. Yet correlations between what we see and what questions we ask—“ideological” Bayesian updating—can lead to predictable biases and polarization.

Professor Polder is a polarizing figure.

His fans praise him for his insight; his critics denounce him for his aggression.

Ask his fans, and they’ll supply you with a bunch of instances when he made an insightful comment during discussions. They’ll admit that he's sometimes aggressive, but they can’t remember too many cases—he certainly doesn’t seem any more aggressive than the average professor.

Ask his critics, and they’ll supply you with a bunch [...]

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Outline:

(03:26) Limited-Attention Bayesians

(06:55) Ideological Bayesians

(12:36) What happens?

(17:12) What to make of this?

(20:00) What next?

The original text contained 3 footnotes which were omitted from this narration.

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First published:

Source:

Linkpost URL:
https://kevindorst.substack.com/p/ideological-bayesians

Narrated by TYPE III AUDIO.