SCAIHOSOC-PHNCMar 31, 2020

Epistemic Phase Transitions in Mathematical Proofs

arXiv:2004.00055v23 citations
AI Analysis

This addresses a foundational problem in cognitive science and philosophy of mathematics regarding how complex beliefs are justified, though it is incremental in applying existing models to a new domain.

The paper tackles the paradox of error probability in mathematical proofs by showing that belief formation can undergo an epistemic phase transition, leading to near-complete confidence at reasonable error rates, as demonstrated through analysis of 48 machine-aided proofs and 5 hand-constructed cases.

Mathematical proofs are both paradigms of certainty and some of the most explicitly-justified arguments that we have in the cultural record. Their very explicitness, however, leads to a paradox, because the probability of error grows exponentially as the argument expands. When a mathematician encounters a proof, how does she come to believe it? Here we show that, under a cognitively-plausible belief formation mechanism combining deductive and abductive reasoning, belief in mathematical arguments can undergo what we call an epistemic phase transition: a dramatic and rapidly-propagating jump from uncertainty to near-complete confidence at reasonable levels of claim-to-claim error rates. To show this, we analyze an unusual dataset of forty-eight machine-aided proofs from the formalized reasoning system Coq, including major theorems ranging from ancient to 21st Century mathematics, along with five hand-constructed cases including Euclid, Apollonius, Hernstein's Topics in Algebra, and Andrew Wiles's proof of Fermat's Last Theorem. Our results bear both on recent work in the history and philosophy of mathematics on how we understand proofs, and on a question, basic to cognitive science, of how we justify complex beliefs.

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