Anthropic submits AI accountability recommendations to NTIA, covering evals, red teaming, and pre-registration
Anthropic submitted a formal response to the NTIA's Request for Comment on AI Accountability, outlining a multi-part policy framework for governing advanced AI systems. Key recommendations include increased government funding for evaluation research, mandatory disclosure of evaluation methods, pre-registration of large training runs with national governments, mandated external red teaming before model release, and antitrust guidance to enable industry safety collaboration. The submission reflects Anthropic's core policy positions and advocates for risk-tiered oversight proportional to model capabilities.
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Anthropic Responds to White House AI Action Plan, Calls for Transparency Standards and Export Controls
Anthropic published a policy response to the White House's 'Winning the Race: America's AI Action Plan,' endorsing its focus on AI infrastructure, federal adoption, and safety research while urging additional steps on export controls and mandatory AI development transparency standards. The company highlighted alignment between the plan and its prior OSTP submissions, and noted its proactive activation of ASL-3 protections with Claude Opus 4 as evidence that safety and innovation are compatible. Anthropic called for a single national standard for frontier model transparency rather than a state-by-state patchwork, and encouraged continued investment in NIST's CAISI for evaluating frontier models on national security risks including CBRN capabilities.
Anthropic submits AI Action Plan recommendations to White House OSTP
Anthropic submitted formal recommendations to the White House Office of Science and Technology Policy in response to its Request for Information on a U.S. AI Action Plan. The submission covers six areas: national security testing of AI models, tightening semiconductor export controls (including H20 chips), enhancing lab security via classified government-industry channels, scaling energy infrastructure to 50 GW by 2027, accelerating government AI adoption, and preparing for economic disruption. Anthropic cites its expectation that powerful AI systems matching Nobel Prize-level intellect will emerge in late 2026 or early 2027, framing the recommendations as urgent national security and economic imperatives.
Anthropic launches initiative to fund third-party AI safety evaluations
Anthropic announced a funded initiative to source third-party evaluations measuring advanced AI capabilities and safety risks, with priority areas including cybersecurity, CBRN threats, model autonomy, national security risks, social manipulation, and misalignment. The initiative is tied to Anthropic's Responsible Scaling Policy and AI Safety Level (ASL) framework, aiming to address a gap between demand and supply of high-quality safety-relevant evals. Proposals are solicited via an application form, with Anthropic framing the effort as benefiting the broader AI safety ecosystem rather than just internal use.
Anthropic responds to California Governor Newsom's AI working group draft report
Anthropic published a formal response to the California Governor's Working Group on AI Frontier Models draft report, endorsing its emphasis on transparency and evidence-based policy. Anthropic argues that light-touch mandatory disclosure of safety and security practices would be beneficial without impeding innovation, noting that current voluntary practices are uneven across frontier labs. The response also references Anthropic's Responsible Scaling Policy and Economic Index as examples of existing transparency efforts, and signals urgency given Anthropic's view that powerful AI systems may arrive as early as end of 2026.
Anthropic advocates for third-party testing regime as core AI policy infrastructure
Anthropic published a policy position paper arguing that frontier AI systems require a third-party testing and oversight regime, distinct from self-governance approaches like their own Responsible Scaling Policy. The post outlines what such a regime should include: trusted third-party auditors, precisely scoped tests targeting only the most computationally intensive systems, and international coordination via shared standards and Mutual Recognition agreements. Anthropic acknowledges their RSP is insufficient alone because it relies on single private-sector actors, and calls for industry-wide mandatory testing that would eventually become a legal requirement for wide deployment.
Anthropic publishes policy brief calling for targeted AI regulation within 18 months
Anthropic published a policy position paper arguing that governments have an 18-month window to enact narrowly-targeted AI regulation before risks in cyber and CBRN domains become acute. The post cites rapid capability gains—SWE-bench scores rising from 1.96% to 49% in a year, GPQA scores approaching human expert level—as evidence that frontier models are approaching meaningful misuse thresholds. Anthropic also reviews its Responsible Scaling Policy as a model for adaptive, proportionate risk governance and calls for similar frameworks to be adopted industry-wide and codified in law.
Anthropic proposes federal AI transparency framework with mandatory Secure Development Frameworks and system cards
Anthropic published a policy proposal calling for a targeted AI transparency framework applicable at federal, state, or international levels, targeting only the largest frontier AI developers (suggested thresholds: ~$100M annual revenue or ~$1B R&D/capex). The framework would require covered developers to publicly disclose a Secure Development Framework covering CBRN and misalignment risks, publish system cards at deployment, self-certify compliance, and face legal liability for false statements. The proposal is explicitly lightweight and flexible, designed to avoid prescriptive standards while creating accountability mechanisms and whistleblower protections during the period before comprehensive safety standards are established.
Anthropic publishes frontier model security recommendations including multi-party authorization and secure development frameworks
Anthropic released a policy and technical guidance document outlining cybersecurity best practices for securing frontier AI models, including multi-party authorization to AI-critical infrastructure, adoption of NIST SSDF and SLSA supply chain standards, and public-private cooperation modeled on critical infrastructure sectors. The post argues that advanced AI models warrant security levels far exceeding standard commercial practices and recommends government procurement requirements as a near-term enforcement mechanism. Anthropic states it is actively implementing these controls internally and calls on other labs and governments to adopt similar frameworks.