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Evidence record 10468 · automatically gathered

Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?

As Large Language Models (LLMs) are increasingly deployed as autonomous agents in high-stakes domains, understanding contextual factors that may modulate their decision-making becomes critical. While LLMs are trained to perceive and resonate with users' emotions, it remains unclear whether induced emotion can influence their sequential decision-making. We investigate this question using the Iowa Gambling Task (IGT), a classic psychological paradigm for studying decision-making under uncertainty,

Record details

Published: 14 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Bias & fairness · Agents & autonomy · Finance, VC & PE
Retrieved: 15 July 2026

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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.

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How to cite this record

ethics.ai (14 July 2026), “Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?,” evidence record 10468, https://ethics.ai/record/10468 (originally published by arXiv cs.AI).

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