We analyze three prominent strategies for governing transformative AI (TAI) development: Cooperative Development, Strategic Advantage, and Global Moratorium. We evaluate these strategies across varying levels of alignment difficulty and development timelines, examining their effectiveness in preventing catastrophic risks while preserving beneficial AI development.

Our analysis reveals that strategy preferences shift significantly based on these key variables. Cooperative Development proves most effective with longer timelines and easier alignment challenges, offering maximum flexibility and minimal intrinsic risk. Strategic Advantage becomes more viable under shorter timelines or moderate alignment difficulty, particularly when international cooperation appears unlikely, but carries the most intrinsic risk. Global Moratorium emerges as potentially necessary in scenarios with very hard alignment or extremely short timelines, but is the least intrinsically viable. The paper also examines the transitional possibilities between strategies and their implications for current policy decisions. This analysis provides a framework for policymakers and AI governance stakeholders to evaluate and adapt their approaches as new information about alignment difficulty and development timelines emerges.

Summary

AI governance strategies are broad plans guiding the AI governance community’s efforts to influence Western governments (e.g., the UK, US, and allies), sub-national groups (e.g., California), the international community (e.g. the annual AI safety summits), and leading AI labs. These strategies aim to direct advocacy efforts toward paths that eliminate AI-related existential risks. We have identified three which implicitly underlie the majority of AI governance advocacy or research:

Cooperative Development (CD): This strategy advocates for regulating TAI development through national and international mechanisms to secure capabilities advantages for trustworthy developers. These developers would use their advantage to create aligned, powerful TAI systems capable of protecting against unaligned or misused AI, ensuring they are deployed widely and effectively. These TAIs would fulfill several goals: limiting the growth of dangerous AI by performing key economic tasks, defending against physical or informational attacks, and ensuring the alignment of other AI systems. CD also s

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