Anthropic proposes ambitious federal funding increase for NIST AI measurement and standards
Anthropic published a policy proposal in April 2023 calling for a significant increase in federal funding for the National Institute of Standards and Technology (NIST) to support AI measurement, evaluation, and standards work. The post argues that rigorous AI capability and risk measurement is a prerequisite for effective regulation, and outlines a concrete funding program building on NIST's existing AI Risk Management Framework and related work. Anthropic frames this as a 'shovel-ready' complement to broader AI governance proposals, recommending at minimum a $15 million increase over FY2023 levels.
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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.
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 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 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 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 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 Donates $20 Million to Public First Action for AI Policy Advocacy
Anthropic is contributing $20 million to Public First Action, a new bipartisan 501(c)(4) organization focused on AI governance and public education. The donation is intended to support policies including AI model transparency requirements, a federal AI governance framework, export controls on AI chips, and targeted regulation of high-risk AI applications such as bioweapons and cyberattacks. Anthropic frames the move as consistent with its safety mission, noting that effective AI governance would increase scrutiny of frontier AI companies including itself. The organization is led by both Republican and Democratic strategists and will work across party lines.
Anthropic publishes 'Build AI in America' energy and infrastructure policy report
Anthropic released a policy report calling for major U.S. investments in energy infrastructure to support frontier AI development, projecting that the U.S. AI sector will need at least 50GW of electric capacity by 2028. The report proposes two strategic pillars: building large-scale AI training infrastructure on federal lands with accelerated permitting, and broader nationwide AI deployment infrastructure including geothermal, natural gas, and nuclear expansion. Anthropic discloses internal projections that single advanced model training will require 2GW data centers in 2027 and 5GW in 2028, framing the recommendations in the context of competition with China's rapid energy buildout.