Risky Business: Measuring The Faithfulness-Safety Tension

Chain-of-Thought (CoT) reasoning offers a promising window into model monitoring. However, monitoring relies on faithfulness, i.e., the model output strictly derives from its reasoning trace. We identify an alignment tension where a model must be faithful enough to be monitored, yet robust enough to reject unsafe reasoning. We demonstrate that this counterbalance exists in current Large Reasoning Models (LRMs), and show ways in which it can be addressed. We introduce HazMart, a human-written dat

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ethics.ai (4 August 2026), “Risky Business: Measuring The Faithfulness-Safety Tension,” evidence record 16268, https://ethics.ai/record/16268 (originally published by arXiv).

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