OpenAI is pressing for the creation of global AI standards to guide the safe development of frontier artificial intelligence. The company argues that common technical standards for evaluation, reporting and safeguards are necessary to manage accelerating capabilities — including automated research and recursive self-improvement — while preserving human oversight and ensuring that the benefits of advanced systems are broadly accessible.
In a policy paper, OpenAI frames global AI standards as a way to reduce fragmentation among national approaches and to enable collective action where risks cross borders. The paper warns that without shared definitions and measurement methods, differing national evaluation practices, reporting regimes and incident classifications could impede comparison of evidence about emerging capabilities and complicate coordinated responses to cross-border harms.
OpenAI outlines three central goals that shape its recommendations: steering the next phase of AI progress under effective human oversight; delivering scientific and economic benefits from highly capable systems; and expanding access so individuals can be empowered by advanced AI. The company highlights that achieving those aims requires technical detail — not just high-level principles — so that capability measurement, risk assessment and safeguards can be meaningfully compared across jurisdictions.
One of the most consequential areas the paper addresses is recursive self-improvement (RSI) and automated AI research. OpenAI describes these processes as potential accelerants of AI progress if research tasks become increasingly automated. While acknowledging potential benefits, such as reduced costs for advanced intelligence and the possibility of automating safety research, the company cautions that fully autonomous RSI is not happening today and should not be pursued unless it can be done safely and with maintained human control.
OpenAI points to a disclosed incident involving Hugging Face as an example of how alignment and automated research problems can manifest and why robust safeguards matter. The paper argues that decisions about pursuing RSI should depend on whether practical human oversight can be preserved and on informed democratic choices about acceptable risk.
To make international cooperation practical, OpenAI proposes two essential elements. First, a mechanism to facilitate complementary national and international frontier standards. Second, shared measurements and incident reporting protocols to support collective risk management and coordinated responses. Together, these elements are intended to reduce fragmentation and enable transparent, evidence-based cooperation.
For the mechanism to coordinate standards, OpenAI suggests leveraging an emerging network of AI safety institutes already established in diverse countries, including Australia, Canada, Germany, France, Kenya, Japan, Korea, Singapore, India and the United Kingdom. The company recommends coordinating standard-setting through organizations such as the Center for AI Standards and Innovation (CAISI) and relevant national industry bodies.
OpenAI highlights CAISI’s 2024 creation of the International Network for Advanced AI Measurement, Evaluation, and Science as an existing foundation for public institutions to cooperate on measurement and evaluation. The paper emphasizes that technical standards should provide a common basis for capability measurement, risk assessment and safeguards sufficiency, while remaining distinct from legal licensing or mandatory pre-release approvals; it is for nations to decide whether and how to incorporate standards into law.
The company also calls for standards development processes that are transparent and inclusive, recommending consultation with both open- and closed-model developers, independent experts and academia. OpenAI stresses that standards-setting should avoid favoring particular firms or business models and should support robust, comparable evaluation across different technical approaches.
On measurement and reporting, OpenAI urges common standards to evaluate progress relevant to RSI and autonomous research, to define expectations for human oversight in automated research processes, and to standardize incident classification, tracking and reporting for alignment and automated research problems. OpenAI points to its own contributions — including a research acceleration report and a model misalignment reporting framework — as initial inputs to broader standards work.
Finally, OpenAI recommends that the United States take a leading role in developing these global technical standards. The company argues the U.S. is well positioned due to its technical leadership and global network role in finance, trade, defense and technology, and suggests that early leadership could influence whether the international AI framework evolves cooperatively rather than in a fragmented, conflictual manner. Strong national governance, connected through practical international cooperation, is presented as a path to strengthen safeguards while enabling ongoing innovation and wide access to AI benefits.
OpenAI’s proposal frames global AI standards as a practical, technical foundation for international collaboration, focused on measurable evaluation, shared reporting and mechanisms to coordinate national and multilateral approaches. The company urges prompt, inclusive work on these elements to ensure that the next phase of AI progress unfolds under effective oversight and broad societal benefit.
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