Theoretical analysis reveals foundational challenges in prior selection within Bayesian prediction frameworks, highlighting persistent obstacles posed by gruesome hypotheses.
I explain basic problems of inductive reasoning from a Bayesian point of view. To make probabilistic predictions, we need to start with a prior, but which prior should we choose? I discuss some natural options and the problems they face, with particular attention to 'gruesome' alternatives.
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Sven Neth (2026) studied this question.
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