Unlearning and Seyab's theorem: a dialogue about updating probability

TL;DR

This paper discusses the concept of unlearning in probability updates, examining how reversing the roles of prior and posterior probabilities can influence the process of updating beliefs.

Contribution

It introduces a novel perspective on probability updating by exploring unlearning and Seyab's theorem through a dialogue format.

Findings

Reversing prior and posterior probabilities affects the updating process.

Unlearning can be formalized within probability theory.

Seyab's theorem offers insights into probability reversal.

Abstract

This dialogue explores the possibility of updating a probability as a consequence of unlearning, reversing the role of prior and posterior probabilities.