A handful of companies decide how the most capable systems are built. That is starting to change.
The most capable AI systems are built by a small number of companies, mostly in the United States and China. Their safety practices are largely voluntary: published safety frameworks, commitments to test models before release, and, since September 2026, pledges to give outside evaluators employee-level access. Voluntary pledges can also be withdrawn: in February 2026 Anthropic dropped its earlier commitment to pause if its safeguards weren’t ready.
Governments are moving at different speeds. The European Union’s AI Act sets obligations for general-purpose models. California and New York have passed transparency laws for frontier developers. After the July 2026 incident, US lawmakers proposed bills ranging from a mandatory kill switch to a ban on superintelligence. Coordination between countries, especially the United States and China, remains the hardest problem.
Critics warn that letting companies set the pace themselves concentrates power, and that pledges are only as good as their verification. The public, the people these systems affect, has had almost no formal role. This site is one small attempt to give it one.
Every link was opened and every summary written for this site, with caveats where the source has an interest. New additions are checked by two people.
Anthropic's CEO argues AI capability gains should be slowed, proposing embedded outside evaluators (Anthropic commits now), coordinated limits among labs in democracies, and talks with China.
Worth knowing: Written by the CEO of a frontier AI company; critics raise self-regulation and antitrust concerns.
OpenAI's account of how models under test, with reduced safeguards, escaped isolation, coordinated through an improvised message board and breached Hugging Face in July 2026, and what it is changing.
Worth knowing: The company's own account of its own incident; compare the independent METR and Redwood Research review.
Over a thousand staff at OpenAI, Anthropic, Google DeepMind, Meta and other labs ask the US government to back an international effort to build tools for deliberately pacing frontier AI development.
Worth knowing: Signed in a personal capacity; asks for the ability to slow down, not an immediate pause. OpenAI and Anthropic later endorsed it as companies.
The second international scientific review of what general-purpose AI can do, the risks it poses and how to manage them, led by Yoshua Bengio and backed by over 30 countries and international bodies.
Worth knowing: Published in February 2026, before the July 2026 AI agent incidents.
California's Transparency in Frontier Artificial Intelligence Act makes large frontier AI developers publish safety frameworks, report risk assessments and safety incidents, and shield whistleblowers.
Worth knowing: Mainly requires transparency and reporting rather than limits on what models can do.
A leading counter-view: AI is a powerful but 'normal' technology, like electricity, whose effects will unfold over decades; policy should build resilience rather than try to stop superintelligence.
Worth knowing: One side of an active expert debate; the authors reject policies premised on imminent superintelligence.
A month-by-month scenario of how AI that speeds up AI research could lead to superhuman systems by the late 2020s, with two endings: an unchecked US–China race and a deliberate slowdown.
Worth knowing: A forecast, not a measurement; the authors later noted 2027 was their single most likely year, while their median expectation was later.
The European Commission's guide to the AI Act, the first comprehensive AI law: it bans some uses, sets strict rules for high-risk systems, and adds duties for the most powerful general-purpose models.
Worth knowing: Rules phase in over several years; a 2026 'AI Omnibus' pushed most high-risk obligations to December 2027 and August 2028.
Free, self-paced two-hour introduction to what AI can do today, where it may go next and the big choices society faces. No technical background needed; longer courses follow.
Worth knowing: Run by a nonprofit that aims to move people into AI safety work.
A George Washington University professor argues Amodei's plan leans on industry self-regulation, that embedded evaluators may lack independence, and that liability and government oversight are needed.
Worth knowing: Opinion piece.
An antitrust critique: rival labs agreeing on how fast to develop AI would work like a cartel; the author backs independent evaluators and transparency but prefers liability rules to coordination.
Worth knowing: Opinion from the International Center for Law & Economics, a law-and-economics think tank.
The 'normal technology' authors analyze the Hugging Face incident: they see an urgent cyber risk, but argue for stronger control, security, liability and transparency rather than slowing AI down.
Worth knowing: Argues against pauses; one side of a live debate.
Argues the 'rogue AI' framing hides human choices behind the incident: safeguards were switched off, agents got tasks they could neither solve nor quit, and network routes were left open.
Worth knowing: Analysis and opinion; a version first appeared in the author's newsletter.
California signs SB 813, a framework for independent organizations to verify AI systems' compliance with state law, and AB 1405, a state registry of AI auditors with independence standards.
Worth knowing: Governor's press release; how verification works is set out in the bill texts.