The Game Theory of AI Pacing (www.paradigm.xyz)

Recent discussions among major AI labs, including Anthropic and OpenAI, have highlighted the need for a coordinated slowdown in frontier AI research due to growing safety concerns. The debate over voluntary deceleration raises questions about the motivations behind AI companies' decisions, which can be elucidated through the lens of game theory. A new multiplayer web game inspired by research from Drew Fudenberg and Andrew Koh models AI labs as competitors deciding whether to accelerate or decelerate their development. The game suggests that while firms strive to be economically competitive, the risk of catastrophic outcomes looms large, creating a complex interplay of competition and cooperation. The game's mechanics reveal substantial challenges in regulating AI progress, such as delayed transparency regarding competitors' advancements and the irreversible nature of development choices. With hurdles like varying degrees of risk perception and the unpredictable nature of the safety frontier, AI labs may find it increasingly difficult to align their pacing. This dilemma is further complicated in the geopolitical arena, where multiple countries, particularly the U.S. and China, are engaged in a race for AI supremacy. The insights from this study underscore the critical need for international cooperation and transparency to mitigate risks associated with unchecked AI development.