Chain-of-thought faithfulness evaluations are valid proxy measures of chain-of-thought monitorability.
Assessment
The evidence weighs against the claim, but the examination is incomplete or the evidence is indirect.
The claim holds that evaluations of chain-of-thought faithfulness, the most common being hint-verbalization tests that check whether a model's reasoning admits to using an inserted cue that changed its answer, are valid stand-ins for how well a monitor can detect target behavior from the reasoning. Faithfulness evaluations have been proposed in this role, most explicitly by Meek et al. (2025), who measure monitorability through faithfulness and verbosity, and in the 2025 multi-author position paper on chain-of-thought monitorability.
The evidence weighs against treating them as valid proxies without further validation. First, the two properties are defined differently: faithfulness concerns whether the trace reflects the computation behind the answer, while monitorability concerns whether a given monitor can detect a given behavior from what it sees, which also depends on the monitor, the behavior, and the task. Second, they have been observed to come apart in both directions. Hint-verbalization studies report low faithfulness in easy settings where the cue can be used without much reasoning, yet Emmons et al. (2025) found that when bad behavior requires multi-step reasoning, the reasoning becomes exposed and monitors catch it, and they argue the relevant property for runtime monitoring is monitorability rather than faithfulness. Li et al. (2026) report a case where probes and ablations give evidence that reasoning-step content is internally represented and causal, yet a monitor with the reference answer did no better than the majority baseline, and another case where a monitor succeeds while mechanistic analyses fail to verify faithfulness. Third, no published study appears to have shown that scores on faithfulness benchmarks predict monitor detection rates across models or tasks; dedicated monitorability evaluations, such as the suite OpenAI released in late 2025, measure monitor performance directly instead.
Faithfulness is still plausibly correlated with monitorability: a trace that omits decisive factors limits what any monitor can see. The supported reading is that faithfulness evaluations are at most partial, unvalidated indicators. What would change this verdict is a study showing that faithfulness scores track measured monitor recall across a range of models, behaviors and monitors.
Full reasoning: the evidence and decisions behind this verdict
What the evaluations measure: the standard faithfulness tests (Turpin et al. 2023; Chen et al. 2025, "Reasoning models don't always say what they think") insert a hint and score whether the reasoning mentions it when the answer changes. Meek et al. 2025 (arXiv 2510.27378) explicitly frame such faithfulness plus verbosity as a measure of monitorability; Li et al. 2026 (arXiv 2611.01620) note "Faithfulness evaluations have been discussed as proxies for monitorability" citing Korbak et al. and Meek et al., and argue "These approaches answer different questions. Using evidence for one property to support a claim about another therefore needs justification."
Divergence evidence: Emmons et al. 2025 (arXiv 2507.05246): "for the distinct problem of runtime monitoring to prevent severe harm, we argue the key property is not faithfulness but monitorability"; when the bad behavior is made hard enough to need CoT-as-computation, models expose reasoning and are monitorable. Li et al. 2026: two case studies on three open-weight reasoning models, one with internal-representation and causal evidence but a monitor at majority baseline, one with monitor success (matched by an answer-only rule) but no compact mechanism found. These are small case studies with modest power, and Li et al.'s "faithfulness" is a mechanistic notion distinct from hint-verbalization, so they bear on the general proxy assumption more than on hint tests specifically. Baker et al. 2025 also reported high-recall CoT monitoring of reward hacking in frontier training even as faithfulness studies reported low verbalization rates, another, indirect, divergence.
Validation search: no study found that correlates faithfulness-benchmark scores with monitor recall across models; OpenAI's monitorability evaluations (Guan et al., Dec 2025, arXiv 2512.18311) score monitors directly. Search was brief, so an unfound validation study remains possible; hence doubtful rather than contradicted. Credence 0.25 reflects that faithfulness is plausibly a correlated partial indicator, and "valid proxy" could be read loosely.
Decomposition
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However, for the distinct problem of runtime monitoring to prevent severe harm, we argue the key property is not faithfulness but monitorability.
Responds to hint-verbalization faithfulness results by arguing they measure CoT-as-rationalization, while monitoring severe harm depends on CoT-as-computation; raising task difficulty made behavior monitorable despite low faithfulness in easier setups.
Faithfulness evaluations have been discussed as proxies for monitorability
The paper cites Korbak et al. and Meek et al. treating faithfulness evaluations as proxy measures for monitorability, and argues against reading them that way without justification.
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