By Chris Lehane, Chief Global Affairs Officer at OpenAI
\nOpenAI argues that the rapid rise of machine intelligence requires stronger safeguards and public policy. Technical work inside individual labs is not enough, the article says; governments and companies also need compatible approaches to measuring capabilities, managing risk, preserving human control, and deciding when development should slow or stop.
\nThe article distinguishes current AI-assisted research from fully autonomous recursive self-improvement. It says fully autonomous recursive self-improvement—systems independently driving successive generations of increasingly capable AI—is not happening today and should not be pursued unless it can be done safely. At the same time, AI agents can already perform some tasks that would take skilled researchers several days.
\nOpenAI says that acceleration should be directed toward safety as well as capability. Its stated aim is to build automated AI researchers that work under human supervision to advance deep learning and alignment, making subsequent systems safer, more aligned, and easier to control.
\nThe article calls for common measurements, meaningful human control, and shared safety bars. If a safety bar cannot be met without slowing capability growth, OpenAI says safety should take priority. It also points to proposals involving common testing and independent assessment, stronger cybersecurity, clear incident reporting, national preparedness, and shared measures for tracking progress toward recursive self-improvement.
\nThe conclusion is deliberately urgent: the policy window is open for now, and OpenAI intends to use it.
\n","headings":[{"level":1,"text":"The AI policy window is open. We need to act.","id":"the-ai-policy-window-is-open-we-need-to-act"},{"level":2,"text":"Preparing for recursive self-improvement","id":"preparing-for-recursive-self-improvement"},{"level":2,"text":"Shared standards and national requirements","id":"shared-standards-and-national-requirements"}]}}