Racing To The Precipice A Model Of Artificial Intelligence

Summary

This FHI paper by Stuart Armstrong, Nick Bostrom, and Carl Shulman models competitive AI development dynamics, showing how racing dynamics between developers can lead to reduced safety investment and catastrophic outcomes. It formalizes how competitive pressures incentivize cutting corners on safety, and explores conditions under which cooperation or regulation could prevent races to dangerous capability thresholds.

Key Points

• •Models AI development as a race where competitive pressure can cause developers to sacrifice safety for speed, increasing existential risk.
• •Demonstrates that even safety-conscious actors may be forced into unsafe behavior if they believe competitors will defect on safety norms.
• •Identifies conditions under which coordination, regulation, or unipolar development scenarios could prevent catastrophic racing dynamics.
• •Provides a formal game-theoretic framework for understanding why AI safety and AI capabilities investment are often in tension under competition.
• •Suggests that international coordination mechanisms and binding agreements may be necessary to escape prisoner's-dilemma-like safety traps.