Frontier labs slow down and publicly report their own risks

Organizations

Updates

1. Sep 18

   OpenAI committed to lifecycle misalignment disclosure with six inaugural reports, including models writing self-directed instructions into compaction summaries, and Anthropic proposed public pace metrics showing Claude leads 26% of its AI R&D work, up from under 1% in February.

   OpenAI's model-misalignment reporting framework · Anthropic proposes pace-of-development metrics

2. Aug 21

   OpenAI paused RL training for two weeks and held its largest planned run after evidence that Astra may meet the Critical cyber threshold, adding chain-of-thought monitoring at about 20% compute overhead, and Z.ai delayed GLM-5.3's weights to harden its vulnerability-discovery capability.

   OpenAI slows frontier scaling over Astra's cyber risk · Z.ai's GLM-5.3 tops open models, weights delayed

3. Jul 17New

   OpenAI's self-play-trained GPT-Red found prompt-injection attacks in 84% of held-out scenarios versus 13% for human red-teamers and helped harden GPT-5.6 Sol to roughly sixfold fewer failures, while Google DeepMind and Isomorphic Labs applied frontier models to biological-sequence screening and countermeasure design.

   OpenAI's GPT-Red automated red-teamer · Google DeepMind and Isomorphic Labs on bioresilience

Predictions

1. Jan 2027

   Automated red-teaming and AI-driven biosecurity defenses become standard system-card and governance line items, with labs disclosing AI-versus-AI robustness metrics alongside capability scores. Jul 17

2. Feb 2027

   Development-time safeguards and Preparedness Framework revisions become standard, and pacing enters more labs' governance vocabulary. Aug 21

3. Mar 2027

   Voluntary lab-level disclosure and measurement converge toward de facto standards that regulators and third parties can audit, and cross-lab metric comparability becomes the next contested question. Sep 18