Anthropic Public Record: First wave survey of 52,000 Americans on AI attitudes
Anthropic released results from its first Anthropic Public Record survey, a nationally representative poll of nearly 52,000 Americans conducted in November–December 2025. Key findings: 64% fear AI-induced job loss (top fear in every state), 56% fear cognitive dependency, over 70% support government regulation of AI, and only 15% trust AI companies to self-govern. The survey found broad bipartisan consensus on AI concerns and accountability, with Americans prioritizing legal liability for AI companies and safety over growth. Anthropic plans to repeat the survey regularly and expand internationally.
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Anthropic Launches Economic Index: First Large-Scale Empirical Study of AI's Labor Market Impact
Anthropic has released the Anthropic Economic Index, an initiative tracking AI's effects on labor markets using anonymized data from approximately one million Claude.ai conversations matched to U.S. Department of Labor O*NET occupational tasks. Key findings show AI use is concentrated in software development and technical writing, with 36% of occupations seeing AI use in at least 25% of their tasks, and usage skewing toward augmentation (57%) over automation (43%). The underlying dataset is being open-sourced to enable independent research, and Anthropic is inviting economists and policy experts to contribute to the ongoing initiative. The analysis was enabled by Clio, Anthropic's privacy-preserving internal conversation analysis tool.
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 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 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 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 publishes structured harm assessment framework covering physical, psychological, economic, and societal impacts
Anthropic has released a policy document describing their evolving framework for assessing and mitigating AI harms across five dimensions: physical, psychological, economic, societal, and individual autonomy impacts. The framework complements their existing Responsible Scaling Policy and informs decisions on usage policies, red-teaming, detection, and enforcement. Concrete examples include safeguards for computer use capabilities (fraud, phishing) and a reported 45% reduction in unnecessary refusals in Claude 3.7 Sonnet through improved handling of ambiguous prompts. Anthropic frames this as a work-in-progress and invites collaboration from the broader AI ecosystem.
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.