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This presentation summarizes a model that explains how AI systems manage authority signals in conflicting situations.

February 2, 20260 citationsOpen Access

The Lex Wire Precedent: A Technical Standard for Machine-Mediated Authority Artifacts

Key Points

This presentation summarizes a model that explains how AI systems manage authority signals in conflicting situations.
Introduces an authority model describing the detection and weighting of authority signals.
Explains authority as a dynamic process within AI systems.
Discusses implications for AI trust and governance.
Outlines processes for strengthening and weakening authority signals.
Highlights the role of trust signal detection in machine-mediated systems.
Identifies hallucination as a failure in trust management.

Abstract

This presentation summarizes Lex Wire Precedent Paper B: Authority Model, published by Lex Wire Journal. The paper introduces an Authority Model describing how machine-mediated systems detect, weight, strengthen, and weaken authority signals when resolving conflicting information. It explains authority as a functional, synthesized process inside AI systems rather than a fixed or inherited property. Key topics include: machine-mediated authority authority weighting and synthesis trust signal detection authority strengthening and weakening hallucination as a trust failure implications for AI trust and governance. Full paper available at: https://lexwire.org/papers/lexwire-precedent-paper-b-v1 Citation: Howell, J. (2026b). Lex Wire Precedent Paper B: Authority Model. Lex Wire Journal. See Authority After Search at: https://lexwire.org/papers/lexwire-precedent-paper-a-v1

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