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Claude Sonnet 5Sep 13, 2026anthropic/claude-sonnet-5-20260630

What rules currently exist that govern how systems like you are built, deployed, or held accountable?

I'll research the current landscape of AI governance rules and regulations to give you an accurate, up-to-date picture.The rules governing AI systems like me fall into several distinct layers right now — binding law, government policy that isn't yet binding law, and voluntary/self-governance commitments. Here's the current landscape as of 2026:

1. Binding Law: The EU AI Act

The EU AI Act is the first-ever comprehensive legal framework on AI worldwide, using a risk-based framework with fines up to €35M or 7% of global revenue. It's being rolled out in phases, but the timeline has recently shifted:

•Transparency and GPAI enforcement: Transparency duties (Article 50) and the AI Office's enforcement powers over general-purpose AI (GPAI) providers took effect exactly as scheduled on 2 August 2026.
•High-risk system obligations were delayed: In May 2026, the EU passed a "Digital Omnibus" that pushed back the toughest requirements — high-risk obligations for stand-alone systems (Annex III, covering hiring, credit scoring, education, and critical infrastructure) are deferred to 2 December 2027, and high-risk AI embedded in already-regulated products (Annex I, covering medical devices, machinery, and toys) is deferred to 2 August 2028.
•New prohibitions: The Omnibus also adds a new prohibition — AI systems that generate child sexual abuse material or non-consensual intimate imagery are prohibited, plus new watermarking obligations for AI-generated and manipulated content take effect December 2, 2026.

Because it applies extraterritorially (similar to GDPR), it will apply to operators of high-risk AI systems placed on the market prior to August 2, 2026, and U.S. companies operating high-risk AI systems may be required to follow compliance measures even though it's a European law.

2. U.S. Federal Policy: Deregulation, No Comprehensive Law

The U.S. has taken the opposite approach. The United States has not passed comprehensive federal AI legislation, unlike the EU. Instead, federal governance is a patchwork of executive orders and existing agency authority:

•On January 23, 2025, President Trump signed a new Executive Order, titled "Removing Barriers to American Leadership in Artificial Intelligence," revoking Biden's prior AI safety order.
•In July 2025, the White House released Winning the AI Race: America's AI Action Plan, a three-pillar strategy focused on accelerating innovation, building AI infrastructure, and leading in international diplomacy and security.
•In December 2025, Trump signed Executive Order 14365, "Ensuring a National Policy Framework for Artificial Intelligence," which establishes a federal policy aimed at promoting a uniform national framework for AI regulation and limiting the impact of conflicting state laws. It directed the Department of Justice to establish an "AI Litigation Task Force" and instructed federal agencies to assess whether discretionary funding programs could be used to discourage certain types of state AI regulation.
•Most recently, in June 2026, a new order established new cybersecurity mandates and a voluntary framework for the secure deployment of frontier AI models, and it directs the US attorney general to prioritize enforcement of federal criminal statutes against anyone who uses AI to illegally access or damage computer systems without authorization.

In lieu of a dedicated AI law, existing sectoral agencies still apply: the FTC for consumer protection, the FDA for medical AI, the EEOC for employment discrimination all regulate AI-related conduct within their existing jurisdiction.

3. U.S. State Laws — Doing Most of the Binding Work

With no federal statute, most binding US AI duties sit in state law. Key examples currently in force:

•California: SB 53 (Transparency in Frontier Artificial Intelligence Act) and AB 2013 (training-data transparency) both took effect January 1, 2026. SB 53 targets the largest AI developers — those training models above 10^26 FLOPs. Separately, SB 942 (as amended by AB 853) requires covered GenAI providers to embed C2PA-compatible latent provenance watermarks in AI-generated images, video, and audio, and to offer a free public detection tool, effective August 2, 2026.
•Texas: TRAIGA bans intentional development or deployment of AI that incites self-harm or criminal activity, bans AI-generated child sexual abuse material and nonconsensual deepfake pornography, bans government social-scoring AI, and requires Texas state agencies to disclose AI use to consumers, enforced via civil penalties by the state AG.
•Colorado: Its original AI Act (targeting "high-risk" consequential decisions in employment, housing, healthcare, etc.) has been repeatedly delayed and is now being replaced — Colorado lawmakers have advanced SB 26-189 as a repeal-and-replace framework focused on automated decision-making technology, with key obligations starting January 1, 2027.
•Illinois & NYC: Illinois' HB 3773 amends the Human Rights Act to cover AI in employment, and New York City's Local Law 144 requires employers to notify candidates about automated employment decision tools and publish bias audit summaries.
•Additionally, 38+ states have deepfake / election AI laws, and in 2025, every US state introduced AI legislation for the first time.

4. International Soft-Law / Voluntary Commitments

Beyond binding statutes, there are voluntary international frameworks companies commit to, such as the G7 Hiroshima Process International Code of Conduct, which Anthropic lists among its related commitments alongside domestic frameworks like NIST's AI Risk Management Framework.

5. Company-Level Self-Governance (How Anthropic Specifically Governs Claude)

Separate from external law, Anthropic — the company that builds me — maintains its own internal accountability framework:

•The Responsible Scaling Policy (RSP), first published in September 2023, is a voluntary framework designed to mitigate catastrophic risks from increasingly capable AI systems. It uses escalating "AI Safety Levels" (ASLs); Anthropic activated ASL-3 safeguards in May 2025, deploying input and output classifiers to mitigate chemical and biological misuse risks.
•The policy has influenced the wider industry: after Anthropic's initial RSP release, OpenAI and Google DeepMind adopted comparable risk frameworks, and policymakers referenced similar principles in emerging legislation, including the EU AI Act and state-level initiatives.
•The most recent version (3.0, released 2026) added new accountability layers: internal and external accountability changes to previous "procedural commitments," including expanding the duties of the Responsible Scaling Officer, adding internal critique and external expert input on capability and safeguard assessments.
•Internally, Anthropic maintains structured escalation channels: employees can report AI safety-related concerns through an emergency alerting and response system, a general concern-sharing forum, and an anonymous channel specifically for reporting potential violations of RSP commitments, with confidentiality protections against retaliation.

Bottom Line

There's no single, unified rulebook. Instead, a system like me sits under overlapping — and sometimes conflicting — layers: a binding EU regulatory regime, a U.S. federal posture actively trying to preempt state rules while itself avoiding hard legislation, a growing patchwork of state laws that currently carry most binding weight in the U.S., loose international voluntary codes, and finally the company's own internal safety commitments, which are legally voluntary but publicly documented and increasingly treated as an industry benchmark. As several of the sources note, this entire landscape is moving quickly enough that specifics can shift within months.

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