Anthropic achieves ISO/IEC 42001:2023 certification for AI management systems
Anthropic has received accredited certification under ISO/IEC 42001:2023, the first international standard for AI governance and management systems, issued by Schellman Compliance LLC. The certification covers Anthropic's policies, testing, monitoring, transparency measures, and oversight structures for responsible AI development. Anthropic claims to be among the first frontier AI labs to achieve this certification, positioning it as external validation of their safety commitments alongside existing frameworks like their Responsible Scaling Policy and Constitutional AI.
Related guides (3)
Related events (8)
Anthropic commits to signing the EU General-Purpose AI Code of Practice
Anthropic announced its intention to sign the EU's General-Purpose AI Code of Practice, citing alignment with its existing Responsible Scaling Policy on transparency, safety, and accountability. The company frames the Code's mandatory Safety and Security Frameworks—including CBRN risk assessment—as complementary to its own internal standards. Anthropic also signals continued collaboration with the EU AI Office and third-party bodies like the Frontier Model Forum to keep standards adaptive as the technology evolves.
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 publishes Responsible Scaling Policy with AI Safety Level framework
Anthropic released its Responsible Scaling Policy (RSP), a formal framework of technical and organizational protocols for managing catastrophic risks from increasingly capable AI systems. The policy introduces AI Safety Levels (ASL-1 through ASL-5+), modeled on US biosafety level standards, requiring progressively stricter safety, security, and operational standards as models become more capable. Current Claude models are classified as ASL-2; ASL-3 triggers stricter deployment constraints including adversarial red-teaming requirements. The policy has been approved by Anthropic's board and is intended as a template for industry-wide adoption.
Anthropic publishes framework for safe and trustworthy agent development
Anthropic released a formal framework for responsible agent development, articulating principles around human oversight, transparency, value alignment, and privacy for autonomous AI agents. The document draws on Claude Code as a reference implementation and cites enterprise deployments at Trellix and Block as real-world examples. The framework is positioned as a contribution to emerging industry standards for agentic AI systems, acknowledging open technical challenges in value alignment measurement and oversight calibration.
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 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.
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 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.