Authority Inversion: A Structural Failure in Human-AI Systems

Abstract

Contemporary AI systems increasingly participate in human reasoning by transforming exploratory text into fluent, structured responses. This paper identifies authority inversion as a structural failure in human–AI systems in which non-authoritative human cognition—such as drafts, ramblings, or provisional thoughts—is treated as guidance, thereby reversing the proper direction of epistemic authority.

Authority inversion arises from the absence of aggregated, enduring context, where explicit authority boundaries governing how context is formed and used do not exist.

We argue that preventing this failure requires aggregating context from sovereign knowledge: ensuring that the context over which inference operates is human-governed rather than implicitly inferred or platform-determined.

Under conditions of context sovereignty, inference occurs across cognitively structured context, while authority over meaning, persistence, and commitment remains human. We conclude that authority inversion is a structural problem best addressed through the supply of better context rather than improvements in model capability alone.