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Evidence record 7009 · automatically gathered

I Can't Believe It's Corrupt: Evaluating Corruption in Multi-Agent Governance Systems

Large language models are increasingly proposed as autonomous agents for high-stakes public workflows, yet we lack systematic evidence about whether they would follow institutional rules when granted authority. We present evidence that integrity in institutional AI should be treated as a pre-deployment requirement rather than a post-deployment assumption. We evaluate multi-agent governance simulations in which agents occupy formal governmental roles under different authority structures, and we s

Record details

Published: 19 March 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026

source-onlyevidence status

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.

Shared topic: Regulation · Shared topic: Agents & autonomy

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How to cite this record

ethics.ai (19 March 2026), “I Can't Believe It's Corrupt: Evaluating Corruption in Multi-Agent Governance Systems,” evidence record 7009, https://ethics.ai/record/7009 (originally published by arXiv).

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