2026 AAAI AAAI 2026

The Fixed-Point of Distrust: A Formal Theory of Perceived Systemic Incompetence

Abstract

Abstract A widespread social sentiment suggests our world operates like a "makeshift world" —a system rife with hidden incompetence. Is this perception an inevitable outcome of our information ecosystem? This paper presents a formal mathematical theory to answer this question affirmatively. We model belief dynamics as a system of interacting agents governed by two operators: (1) an Attentional Update Operator formalizing how negatively biased information is assimilated, and (2) a Social Aggregation Operator modeling belief fusion over a network. Our main contribution is a rigorous proof: under minimal systemic negative bias and standard network connectivity, the collective belief system is a contraction mapping, guaranteed to converge to a unique pessimistic fixed-point that perceives the world as incompetent, regardless of objective truth. This work establishes a mathematical foundation for understanding systemic perceptual biases with applications to platform design and policy.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning
🧭 Keyword Pioneer — network aggregation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy

Authors