The field of AI research is moving towards a greater emphasis on safety and fairness, with a focus on developing innovative solutions to address the risks associated with advanced AI systems. Researchers are exploring new approaches to verify international agreements about AI development, ensuring that countries can trust each other to follow agreed-upon rules. There is also a growing recognition of the need to move beyond traditional notions of equality in machine learning fairness, towards a more nuanced understanding of egalitarianism and its implications for AI systems.

Noteworthy papers in this area include: The paper 'What Is the Point of Equality in Machine Learning Fairness? Beyond Equality of Opportunity' which proposes a multifaceted egalitarian framework for ML fairness. The paper 'Toward a Global Regime for Compute Governance: Building the Pause Button' which proposes a concrete framework for a global 'Compute Pause Button' to prevent dangerously powerful AI systems from being trained.