Moving AI governance forward

1) Commit to internal and external red-teaming of models or systems in areas including misuse, societal risks, and national security concerns, such as bio, cyber, and other safety areas.

Companies making this commitment understand that robust red-teaming is essential for building successful products, ensuring public confidence in AI, and guarding against significant national security threats. Model safety and capability evaluations, including red teaming, are an open area of scientific inquiry, and more work remains to be done. Companies commit to advancing this area of research, and to developing a multi-faceted, specialized, and detailed red-teaming regime, including drawing on independent domain experts, for all major public releases of new models within scope. In designing the regime, they will ensure that they give significant attention to the following:

• Bio, chemical, and radiological risks, such as the ways in which systems can lower barriers to entry for weapons development, design, acquisition, or use

• Cyber capabilities, such as the ways in which systems can aid vulnerability discovery, exploitation, or operational use, bearing in mind that such capabilities could also have useful defensive applications and might be appropriate to include in a system

• The effects of system interaction and tool use, including the capacity to control physical systems

• The capacity for models to make copies of themselves or “self-replicate”

• Societal risks, such as bias and discrimination

To support these efforts, companies making this commitment commit to advancing ongoing research in AI safety, including on the interpretability of AI systems’ decision-making processes and on increasing the robustness of AI systems against misuse. Similarly, companies commit to publicly disclosing their red-teaming and safety procedures in their transparency reports (described below).

8) Develop and deploy frontier AI systems to help address society’s greatest challenges