The field of AI safety is rapidly evolving, with a growing emphasis on developing international agreements and regulatory frameworks to mitigate the risks associated with advanced AI systems. Researchers are exploring various approaches to regulate AI development, including conditional treaties, incident regimes, and safety standards. A key direction in the field is the development of frameworks that balance the need for innovation with the need for safety, with some proposals focusing on establishing risk thresholds, auditing, and verification processes. Another important area of research is the analysis of the efficacy of different regulatory approaches, including the potential for weak safety regulation to backfire. Notable papers in this area include:

• A proposal for a conditional AI safety treaty that establishes a compute threshold for rigorous oversight, and mandates audits of models and governance practices.
• A study that examines the interactions between regulators, AI technology creators, and domain specialists, and finds that weak safety regulation can have unintended consequences, while stronger regulation can lead to safety and performance gains.