Induced Emotion Has Subtle, Conditioned Effects on LLM Decision-Making in Sequential Tasks

Jul 15, 2026

A preprint study used the Iowa Gambling Task to test whether induced emotions bias large language model (LLM) decision-making. The researchers found that, unlike humans, LLMs do not show significant average bias from induced emotion. However, anger specifically made LLMs less sensitive to penalties and reduced their early-stage exploration, leading to more rigid choices. The study also validated a new paradigm for studying affective influences on LLMs.

Why it matters: Understanding how emotional context affects LLM decision-making is important for ensuring the safety and reliability of autonomous AI agents in real-world applications.

Full story at: arXiv Computation and Language ↗