11 Sep 2026

Digest: Anthropic misuse report, California enacts AI verification law

1. Anthropic's threat report details Claude misuse for missile guidance code, an autonomous drone swarm, national surveillance and mass distillation Recommended

   Anthropic's most detailed misuse report yet covers operations disrupted from December 2025 to August 2026: a suspected Russian state actor whose Claude Code workflows rebuilt malware whenever detected, across 20+ government and defence targets; a Yemen-based cell using Claude Code instead of engineers to write guidance software for a guided rocket and a 2,000 km+ missile; Russia-based freelancers building an FPV 'kamikaze' drone swarm whose onboard model picked targets, including a 'person' class, and issued detonation commands with no human in the loop; a consultant building a surveillance platform for Mali's intelligence service spanning ~25 million SIM cards; five bio cases, one an orthopoxvirus immune-evasion grant application; and distillation by seven China-based labs, the largest (Alibaba) exceeding 151 million exchanges to train Qwen models. All misuse ran on Haiku, Sonnet and Opus; none on Fable or Mythos. Companion evaluations also found Anthropic's top models geolocate images at expert level or better and write flight software that flies a simulated drone through jammed GPS.

2. Newsom signs SB 813 and AB 1405, creating the first US legal framework for independent third-party AI verification

   California Governor Gavin Newsom signed two bills backed by both Anthropic and OpenAI. SB 813 (Sen. Jerry McNerney) establishes a first-in-the-nation framework for 'independent verification organisations' that can assess AI systems and models for compliance with state law and sets up a state AI standards and safety commission; AB 1405 (Asm. Rebecca Bauer-Kahan) creates a state registry of AI auditors with standards for their independence, transparency and integrity. As described by the governor's office, the laws build the infrastructure for third-party evaluation and audits rather than mandating specific audits of frontier models, filling the gap that last year's SB 53 transparency law left open, and McNerney cited this week's incidents involving powerful models and agents as the impetus. Newsom paired the signing with a call for 'robust, national regulations' from Washington. OpenAI announced its support hours before the signing; Anthropic endorsed the bills in August.

   Office of the Governor of California via gov.ca.gov
3. Proposal for tracking the effects of architecture on monitorability

   Redwood Research's Ryan Greenblatt, Alek Westover and Lukas Finnveden propose three transparency commitments for AI companies as recurrent architectures and latent inter-agent communication threaten chain-of-thought monitoring: regularly publish externally verified reports of the 'opaque serial depth' (roughly, how many sequential computation steps a model can perform before anything is written out) of all near-frontier models, including internal R&D prototypes at least as capable as the best public models from six months ago; share monitorability evidence, including stress tests of whether models can be prompted or fine-tuned to reason or communicate covertly, with third-party review every six months; and publish a policy on which architectures could degrade monitorability and how performance is traded against it. Verification would rely on employee interviews and whistleblower channels rather than architecture disclosure. A companion post operationalises the metric. The proposal lands with GPT-6 Astra's recurrence known only from OpenAI's brief 'within a factor of two of GPT-4' statement.

   Ryan Greenblatt via Redwood Research
4. What will our economic future look like?

   Anthropic's Economics team released an interactive scenario explorer and a technical report ('Economic Scenarios for Transformative AI', Korinek et al.) modelling the US economy in 2030 as bundles of O*NET tasks that AI augments, automates, leaves alone or creates. Three scenarios: modest (internet-scale impact, GDP +1.6% vs. baseline), substantial (AI can do half of knowledge work, growth at twice the normal rate, GDP +8.3%, knowledge-worker wages flat) and extreme (AI does nearly all knowledge work autonomously, likely requiring recursively self-improving systems; GDP +32.4%, growth reaching 15% a year, unemployment beyond recession levels). A survey of 10,980 Americans found the median respondent's expectations imply roughly the substantial scenario, with about 10% in line with the extreme one. Caveats the authors and critics raise: the model is silent on policy responses, does not model takeoff dynamics or catastrophic risk, and caps automation inputs at 'almost all' knowledge work, so it cannot express the fastest scenarios some forecasters hold.

   Anthropic