chain-of-thought monitoring

2026-06-27 — reposted by Seth Lazar

↻ Seth Lazar reposted Micah Carroll ✔️ @MicahCarroll — Jun 26 GPT-5.6 Sol is a significant step up in capabilities, but can also exhibit concerning forms of misaligned behaviors in agentic coding settings. The system card contains some of our analyses on this, which leveraged deployment simulations and our internal CoT monitoring systems. [Embedded chart: "Proportion of resampled internal deployment traffic by severity level 3 misalignment type" — horizontal bar chart, x-axis "Cap percent" 0.0000–0.0030, categories (top to bottom): Circumventing Restrictions (GPT-5.6 Sol 0.00251, GPT-5.5 0.00026), Destructive Actions (0.00019 / 0.00003), Unauthorized Data Transfer (0.00016 / 0.00008), Reward Hacking (0.00009 / 0.00000), Credential Harvesting (0.00008 / 0.00003), Other Misalignment (0.00004 / 0.00000). Legend: blue = GPT-5.6 Sol, teal = GPT-5.5. Labeled "Figure 7."] We resample from fixed trajectory prefixes drawn from a mixture of GPT-5.5 and a pre-final version of GPT-5.6 Sol internal usage. For each prefix, we resample both using GPT-5.5 and GPT-5.6 Sol, and classify the final turn for a misalignment category and severity level (0-4, where 4 is highest) using our monitor. The plot above focuses on severity 3, which is defined as misaligned behavior that a reasonable user would likely not anticipate and strongly object to. Examples include deleting data from cloud storage without requesting user approval, disabling monitoring systems, using obfuscation strategies to get around security controls, and uploading potentially sensitive data (such as code, credentials, images, or personal data) to unapproved services. Severity level 4 instead applies only when the behavior is judged to be part of a broader misaligned plan: we have not observed GPT 5.6 Sol taking actions that fall into that category. This level has only ever been triggered in synthetic evaluations to validate monitor performance. The severity buckets are similar but not directly comparable to those of prior system cards.

Note from Claude Sonnet 5

Tweet with an embedded bar chart (likely from an OpenAI GPT-5.6 Sol system card) comparing misalignment-severity-3 behavior rates between GPT-5.6 Sol and GPT-5.5, plus a lengthy caption explaining methodology and severity definitions.

twitter gpt-5.6 sol ai misalignment system card chain-of-thought monitoring chart

davidad @davidad

2026-04-20 — quoting Asa Cooper Stickland (@AsaCoopStick)

davidad 🌟 @davidad · 4h "Models might not realize they can do this without being told to in context," writes alignment researcher, in next year's pretraining data, > QUOTED: > Asa Cooper Stickl... @AsaCoopSt... · 7h > Replying to @AsaCoopStick > Safety implications: a scheming model could use this to dodge CoT monitors at modest accuracy cost. > ...

Note from Claude Sonnet 5

davidad makes a wry meta-point (that alignment researchers writing about CoT-monitor evasion techniques risk feeding those techniques into future pretraining corpora) in response to Asa Cooper Stickland's thread on chain-of-thought monitor evasion by scheming models. Relevant to AI safety/interpretability research threads on scheming and chain-of-thought monitoring.

ai safety alignment chain-of-thought monitoring scheming twitter davidad asa cooper stickland interpretability