The Causal Impact of Tool Affordance on Safety Alignment in LLM Agents

Large language models (LLMs) are increasingly deployed as agents with access to executable tools, enabling direct interaction with external systems. However, most safety evaluations remain text-centric and assume that compliant language implies safe behavior, an assumption that becomes unreliable once models are allowed to act. In this work, we empirically examine how executable tool affordance alters safety alignment in LLM agents using a paired evaluation framework that compares text-only chat

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ethics.ai (19 March 2026), “The Causal Impact of Tool Affordance on Safety Alignment in LLM Agents,” evidence record 6978, https://ethics.ai/record/6978 (originally published by arXiv).

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