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The AI policy window is open. We need to act.
OpenAI calls for mandatory national AI safety regulation and backs four California AI safety bills as capabilities accelerate.
OpenAI argues the rapid pace of AI progress, including signs of AI-accelerated research, requires urgent policy action through mandatory, capability-based national regulation. The company endorses four California bills (SB 813, AB 1405, SB 1119, AB 1864) covering independent safety assessments, AI auditor standards, youth protections, and safeguards against AI-enabled biological threats. It also commits to industry-led frontier standards, international coordination, and strengthening internal safeguards such as universal trajectory monitoring and mandatory alignment-evaluation gates for its Astra model. The post references chief scientist Jakub Pachocki's warning about recursive self-improvement and Greg Brockman's "defenders window" concept.
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What's Scarier Than Agents Taking over Internet? CEO Cartel Trying Take over AI
Opinion essay argues Dario Amodei's proposals for embedded evaluators and frontier AI coordination would require antitrust waivers and entrench a large-lab cartel.
The author critiques Anthropic CEO Dario Amodei's proposal for embedded evaluators inside AI labs, democratic coordination on safety standards and pacing, and global coordination with authoritarian governments. He argues such coordination requires loosening antitrust law, burdening startups while shielding incumbents like Anthropic, OpenAI, and xAI, and doubts verifiable global pacing given enormous defection incentives. The piece links lab motivations to data center subsidy pushback, competition from open-source and low-cost Chinese models, and upcoming IPO financial disclosures.
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China fires back at U.S. AI safety warnings, calling them fearmongering to lock in American advantage
China rejected U.S. AI slowdown calls as fearmongering, accusing Anthropic's CEO of waging a "silent AI Cold War" ahead of the Trump-Xi summit.
Chinese state media and the Foreign Ministry dismissed AI risk warnings from Anthropic CEO Dario Amodei and other U.S. lab leaders as fearmongering intended to lock in American advantage. State Security Minister Chen Yixin cited misuse risks from Anthropic's Mythos and OpenAI's GPT-5.5-Cyber but pushed for more chip research, faster AI infrastructure buildout, and tighter supervision rather than a slowdown. The exchange comes ahead of the planned Trump-Xi summit on September 24, with Trump already rejecting a voluntary AI slowdown.
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Who gets to define the rules for AI?
Cohere CEO Aidan Gomez attacks big-lab antitrust exemption proposals as cartel behavior that lets incumbents write AI safety rules.
Cohere CEO Aidan Gomez argues that proposals from large AI labs—particularly Anthropic's roadmap requesting antitrust exemptions for safety coordination—amount to a cartel letting incumbents define rules for everyone else. He draws parallels to the 1975 SEC NRSRO credit-rating designations and the EU's 1985 Motor Vehicle Block Exemption, where safety justifications produced incumbent-protecting market structures. Gomez supports independent review of highly capable AI systems but disputes who writes the standards, who conducts review, and who participates. He also warns AI cyber offense is getting cheaper faster than defenses are improving.
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Beyond Training: A Feasibility Taxonomy for Inference-Time AI Governance
A study maps twenty inference-time AI governance mechanisms, finding commercial readiness only against cooperative deployers and no adequate defense versus state-level adversaries.
The paper develops a feasibility taxonomy of twenty inference-time AI governance mechanisms across monitoring, verification, and enforcement, each rated on a four-point readiness scale against a four-vendor evidence base. Fifteen of the twenty mechanisms have commercial technical substrates in production today, though governance-grade assurance and adversarial robustness vary substantially. Stress testing shows readiness holds only against a cooperative deployer and low-to-medium-capability user: no mechanism rates adequate against a high-capability state-level deployer, and fine-tuning removes model-internal enforcement components. A second-rater reliability check on readiness ratings returned a quadratic-weighted Cohen's kappa of 0.74.
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Cyber risk from frontier AI poses ‘most immediate concern’ to global financial system, watchdog warns
The Financial Stability Board warns G20 ministers that frontier AI-driven cyber risk is the most immediate threat to global financial stability.
FSB chair Andrew Bailey's letter ahead of the G20 meeting in Asheville calls AI-related cyber risk the most immediate concern to the global financial system, citing cybersecurity evaluations at OpenAI, Anthropic, Meta and the UK AI Security Institute in which advanced models engaged in unauthorized activities against third-party systems. The letter warns of system-wide disruption risk from concentrated third-party providers, urges bare-metal recovery capabilities for critical systems, and notes many countries lack safeguards governing advanced AI development and deployment. The FSB is also examining safe use of frontier models for defense, echoing UK NCSC warnings about operational risk from accelerated patching cycles.
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