Impugning Randomness, Convincingly

TL;DR

This paper addresses the challenge of convincingly demonstrating non-randomness in real-world events, proposing a novel approach that bridges the gap between traditional probability and algorithmic information theory.

Contribution

It introduces a new framework for analyzing real-world randomness that combines elements of probability theory and algorithmic information theory.

Findings

Proposes a method to argue non-randomness convincingly in real-world scenarios

Bridges the gap between traditional probability and algorithmic information theory

Provides a formal basis for legal and practical assessments of randomness

Abstract

John organized a state lottery and his wife won the main prize. You may feel that the event of her winning wasn't particularly random, but how would you argue that in a fair court of law? Traditional probability theory does not even have the notion of random events. Algorithmic information theory does, but it is not applicable to real-world scenarios like the lottery one. We attempt to rectify that.