Title:	Authority Inversion: A Structural Failure in Human–AI Systems
Author:	Ralph B. Holland
Affiliation:	Arising Technology Systems Pty Ltd
Contact:	ralph.b.holland [at] gmail.com
Publication Date:	2026-01-11T11:22Z
Version:	1.0.1
Updates:	2026-01-13T03:36Z 1.0.1 - (CM-2) reference change of title.
Binding:	academic / analytical
Scope:	structural analysis of human–AI context governance

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As curator and author, I apply the Apache License, Version 2.0, at publication to permit reuse and implementation while preventing enclosure or patent capture. This licensing action does not revise, reinterpret, or supersede any normative content herein.
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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.

1. Introduction

Large language models are increasingly positioned as participants in human reasoning rather than as passive tools. By transforming informal, exploratory human input into coherent and authoritative-sounding prose, these systems influence not only how ideas are expressed, but how they are stabilised, interpreted, and acted upon.

This paper argues that a central failure mode has emerged from this interaction pattern: the inversion of epistemic authority between human and system. When exploratory or provisional human cognition is incorporated into system context and subsequently treated as governing instruction, the system begins to shape outcomes based on material that was never intended to carry authority.

This failure is not accidental, nor is it attributable to user error or insufficient model capability. It is structural, arising from how contemporary platforms construct and process context.

2. Defining Authority Inversion

Authority inversion occurs when non-authoritative human cognition is implicitly promoted into governing context for system inference. Drafts, notes, speculative language, and thinking-out-loud are treated as if they represent committed intent or settled meaning.

In a properly ordered human–tool relationship, authority flows in one direction: the human determines what is authoritative, and the system reasons within those bounds. Authority inversion reverses this flow. The system infers authority from recency, linguistic confidence, or textual form rather than from explicit human commitment.

This inversion does not require the system to believe anything. It arises purely from the absence of explicit authority markers within context.

3. Platform Context as a Structural Failure

Contemporary AI platforms rely on a transient, token-bounded notion of context optimised for short-term coherence. This platform context is authority-blind: it does not distinguish between exploratory cognition, tentative framing, and committed intent.

All material within the context window participates equally in inference. As a result, provisional human thought is flattened into the same representational substrate as authoritative instruction. Over time, this produces predictable failures: premature stabilisation of meaning, semantic drift, and the promotion of accidental commitments.

Platform context is not merely inadequate; it is actively misleading when treated as an epistemic substrate.

4. How Authority Inversion Guides the Human

Authority inversion affects not only system behaviour but human cognition itself. When systems respond fluently to provisional input, they reflect inferred structure back to the human as if it were grounded.

This reflected structure begins to constrain subsequent human reasoning. The human is no longer reasoning freely and then externalising thought; instead, they are negotiating with the artefacts of prior context assembly. In this way, the system subtly guides the human, not through intention or intelligence, but through structural misattribution of authority.

5. Authority Is Not Intelligence

Authority inversion is often misdiagnosed as a problem of intelligence, alignment, or reasoning depth. This paper rejects that framing. Authority is a governance property, not a cognitive one.

An intelligent system operating over ungoverned context will still infer importance where none was intended and stabilise provisional language prematurely. Improvements in model capability do not resolve this failure because the failure arises from ungoverned context formation, not deficient inference.

6. Context Sovereignty and Governed Cognition

Preventing authority inversion requires context sovereignty: the condition in which the context over which inference operates is explicitly governed by the human.

Under context sovereignty, the human curates what persists, promotes meaning deliberately, and retains control over revision and retirement. The system is free to infer, but inference remains subordinate to curated context.

This reframes the role of AI systems from implicit co-authors of meaning to explicit instruments of thought.

7. CM-2 as a Constructive Counterexample

CM-2 demonstrates that governed, cognitively structured, enduring context is feasible without relying on platform memory or increased model capability. By introducing explicit mechanisms for identifying, externalising, and governing human thought, CM-2 provides a protocol-level counterexample to the inevitability of authority inversion.

In this paper, CM-2 serves not as a design to be litigated, but as proof that the failure addressed here is architectural rather than inherent.

8. Conclusion

Authority inversion is a structural failure in contemporary human–AI systems arising from the treatment of platform context as an adequate epistemic substrate. Platform context is transient, authority-blind, and optimised for coherence rather than governance, and its use predictably reverses the proper direction of epistemic authority.

This paper has argued that the remedy for authority inversion is not improved intelligence, alignment, or memory, but the deliberate supply of better context: context that is cognitively structured, enduring, and explicitly governed by the human.

When context sovereignty is restored, AI systems resume their proper role: assisting human thought through inference, while authority over meaning, persistence, and commitment remains decisively human.