The Anthropic Fallacy: From Bostrom's Theory to the Ethics of Typicality

This article provides an in-depth analysis of the anthropic fallacy, tracing the evolution of Nick Bostrom's thought from the Self-Sampling Principle (SSA) to the Strong Self-Sampling Principle (SSSA). The author explains why switching to counting observational moments rather than individuals avoids logical pitfalls such as the Incubator Paradox and the Boltzmann Brain Problem. The article translates these abstract concepts into practical ground, unmasking selection biases in social data and digital platform algorithms. A key point is the redefinition of the reference class, which is becoming an essential tool for data ethics and the design of fair AI systems. This is a crucial study of the representativeness of epistemic evidence in the technological age.