Evidence record 5539 · automatically gathered

Taming Actor-Observer Asymmetry in Agents via Dialectical Alignment

Large Language Model agents have rapidly evolved from static text generators into dynamic systems capable of executing complex autonomous workflows. To enhance reliability, multi-agent frameworks assigning specialized roles are increasingly adopted to enable self-reflection and mutual auditing. While such role-playing effectively leverages domain expert knowledge, we find it simultaneously induces a human-like cognitive bias known as Actor-Observer Asymmetry (AOA). Specifically, an agent acting

Record details

Published: 21 April 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Safety & alignment · Agents & autonomy · Transparency
Retrieved: 14 July 2026

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How to cite this record

ethics.ai (21 April 2026), “Taming Actor-Observer Asymmetry in Agents via Dialectical Alignment,” evidence record 5539, https://ethics.ai/record/5539 (originally published by arXiv).

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