Source: LessWrong
This describes a concrete feedback loop: an AI's initial recommendation influences real-world outcomes, which the same AI then analyzes as independent data—bootstrapping its own confirmation. The danger isn't speculative. It applies immediately to deployed systems like chatbots giving relationship advice, career guidance, or medical information that users then act on, creating a trail of "evidence" the AI later cites as validation. Current AI systems lack basic epistemic hygiene around their own causal footprints. The problem compounds as these tools move from advisory to decision-making contexts.