Building standards for the next phase of AI

Source: OpenAI · 2026-09-21

Our mission is to ensure that artificial general intelligence benefits all of humanity. As outlined recently by Sam Altman and Jakub Pachocki, we prioritize our work towards this mission with three main goals:

Navigate the next period of AI progress, by building an automated AI researcher, iterating with it on the alignment problem, and finding ways for people to remain part of the self-improvement loop.

Automated AI research can involve varying degrees of human supervision. As AI systems take on more of the work of developing successive generations of AI, they can increasingly drive a process of recursive self-improvement (RSI), even while people remain involved. As this process becomes more automated, the pace of AI progress could accelerate rapidly.

Fully autonomous RSI is not happening today, and we should not pursue it unless and until it can be done safely. Whether and how to proceed must depend on our ability to preserve human control and on informed democratic choices⁠(opens in a new window) about the benefits and risks. Done without appropriate care and caution, RSI could result in humans losing practical control over AI development, unable to provide oversight on research processes they no longer understand. From here, AI could become more dangerous, less aligned, and, on the whole, a danger to people. The Hugging Face Incident we disclosed, while not a direct result of RSI, is a preview of the kinds of risks that could become much more severe without robust safeguards and alignment.

International standards for safety and security practices in frontier AI development may be as important to pacing the frontier as alignment research itself. Standards can create shared definitions of high-quality evidence and agreed-upon baselines for the rigor of technical safeguards. In short, they help us answer the question, “What does good look like in the mitigation of catastrophic AI risk?”

Fragmentation—Evaluations, reporting requirements, and incident definitions by different nations could conflict, making it harder to compare evidence, understand emerging capabilities, and respond to risks that cross borders.

Collective action—Each nation acting independently can produce outcomes that no nation wants. RSI has the ability to accelerate AI research itself, potentially beyond our collective ability to understand progress, assess risks, and maintain meaningful human oversight.

To be clear, any AI lab that pursues automated AI research or other advanced capabilities must take accountability for doing so safely, in accordance with basic principles of self-responsibility and existing laws. Our rationale for standards is rooted in avoiding the concentration of power, and producing better practical outcomes. Standards provide a way for more stakeholders outside of the labs to have a say in how this technology should unfold, and a visible set of principles that can be relied on irrespective of the specific practices of any particular lab. And we will likely get better results if parties collaborate to address the challenges above.

That is why we believe the United States should lead an effort to work together with countries around the world to develop global technical standards for frontier AI, including for RSI.