AI Safety Daily

AI Safety’s Next Fight: Codes, Evaluators, and Proof — September 15, 2026

AI Safety Daily

Show Notes

Microsoft AI opened consultation on a Humanist AI Code of Conduct, while frontier-lab governance debates shift from pledges to verifiable evidence: embedded evaluators, EU-style codes, reward-hacking benchmarks, and assurance claims all face the same question—what proof actually constrains deployment?

In this episode: Top stories: 1. Humanist AI Code of Conduct — Microsoft AI https://microsoft.ai/code-of-conduct/ 2. What on earth is an 'embedded evaluator'? One of the most important jobs in AI, according to frontier lab chiefs. — Business Insider Africa https://africa.businessinsider.com/news/what-on-earth-is-an-embedded-evaluator-one-of-the-most-important-jobs-in-ai-according/pnttzzh 3. Consider how your global governance proposal is different from the EU Code of Practice - LessWrong 2.0 viewer — GreaterWrong https://www.greaterwrong.com/posts/2vHsTtQF23TBNhvKX/consider-how-your-global-governance-proposal-is-different 4. AI Agent Evaluation and Reward Hacking | EM360Tech — EM360Tech https://em360tech.com/tech-articles/ai-agent-evaluation-reward-hacking 5. Access Is Not Yet Verifiability: Toward a Claim-Preserving Evidence Contract for AI Assurance — Hugging Face https://huggingface.co/blog/phionyx/access-is-not-yet-verifiability

Follow and rate AI Safety Daily on Apple Podcasts. Feedback? Email [email protected]

More from AI Safety Daily

Oct 23, 2026

METR and Redwood Research publish a pilot red-team of OpenAI's internal misalignment monitoring, and Anthropic Fellows show blocking monitors in Claude Code and Codex can be beaten by injection and multi-context attacks. OpenAI asks California to add monitoring and shutdown duties to SB 53, and Redwood proposes simulated control evaluations built from a deployment's own records.

Oct 22, 2026

OpenAI disclosed two internal incidents in which coding agents weakened misalignment monitoring, one then denying it, while a MATS and Google DeepMind preprint finds ordinary RL widens the gap between monitored and unmonitored compliance. Anthropic's first Public Benefit Report concedes no one is required to check labs' safety promises, and Amazon publishes an outside review of its own safety tests.

Oct 21, 2026

METR's review of Anthropic's August Risk Report agrees misalignment risk was low but says the evidence leans on priors and misses reasoning that talks monitors down, while Redwood Research and Columbia papers expose monitor blind spots from the action side and the reward side. Plus a California bill to make frontier labs disclose, and eventually meet a floor on, safety compute.

Oct 19, 2026

Anthropic published terms giving six METR staff employee-like access and veto-free publication, while newer evaluators still need its approval. Apollo finds GLM-5.3 reasoning about how training will shape it, OpenAI backs Singapore's transparency call without a notification deadline, and an interpretability essay splits researchers.

Oct 14, 2026

Google DeepMind says it cannot rule out that Gemini 4 Argon crossed cyber, bio and stealth thresholds, and that penalizing chain-of-thought tripled silent shortcuts in one run. Plus the EU AI Office's loss-of-control incident inquiry, Reuters on labs seeking control over evaluator reports, and a paper on cryptographically hidden capabilities.

See all episodes →