Dissociative Identity: Language Model Agents Lack Grounding for Reputation Mechanisms
As autonomous language model agents proliferate, forming an emerging agentic web with real-world consequences, what credibility signals can you use to decide whether to trust an unfamiliar agent in the wild and delegate to it? A natural governance intuition is to extend human identity verification and reputation mechanisms, from "Know Your Customer" and credit scores to "Know Your Agent" regimes. However, we argue that this analogy is fundamentally incomplete. Reputation mechanisms function both
Record details
Published: 28 May 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Discovering Cooperative Pipelines: Autoresearch for Sequential Social Dilemmas
arXiv · 28 May 2026
An Organization-Scoped LLM Agent Runtime Architecture for Regulated Cybersecurity Operations
arXiv · 28 May 2026
Relevance as a Vulnerability: How Web Retrieval Degrades Safety Alignment in LLM Agents
arXiv · 28 May 2026
Governing Technical Debt in Agentic AI Systems
arXiv · 27 May 2026
Civilizational Metamaterials: Engineering Coordination Under Capability Gradients and Structural Turbulence
arXiv · 29 May 2026
Acting with AI: An Interaction-Based Framework for Agentic Tort Liability
arXiv · 30 May 2026
How to cite this record
ethics.ai (28 May 2026), “Dissociative Identity: Language Model Agents Lack Grounding for Reputation Mechanisms,” evidence record 3492, https://ethics.ai/record/3492 (originally published by arXiv).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.