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The Suicide Region: Option Games and the Race to Artificial General Intelligence

Published: December 8, 2025 | arXiv ID: 2512.07526v1

By: David Tan

Potential Business Impact:

Forces AI race to speed up, risking disaster.

Business Areas:
Artificial Intelligence Artificial Intelligence, Data and Analytics, Science and Engineering, Software

Standard real options theory predicts delay in exercising the option to invest or deploy when extreme asset volatility or technological uncertainty are present. However, in the current race to develop artificial general intelligence (AGI), sovereign actors are exhibiting behaviors contrary to theoretical predictions: the US and China are accelerating AI investment despite acknowledging the potential for catastrophic failure from AGI misalignment. We resolve this puzzle by formalizing the AGI race as a continuous-time preemption game with endogenous existential risk. In our model, the cost of failure is no longer bounded only by the sunk cost of investment (I), but rather a systemic ruin parameter (D) that is correlated with development velocity and shared globally. As the disutility of catastrophe is embedded in both players' payoffs, the risk term mathematically cancels out of the equilibrium indifference condition. This creates a "suicide region" in the investment space where competitive pressures force rational agents to deploy AGI systems early, despite a negative risk-adjusted net present value. Furthermore, we show that "warning shots" (sub-existential disasters) will fail to deter AGI acceleration, as the winner-takes-all nature of the race remains intact. The race can only be halted if the cost of ruin is internalized, making safety research a prerequisite for economic viability. We derive the critical private liability threshold required to restore the option value of waiting and propose mechanism design interventions that can better ensure safe AGI research and socially responsible deployment.

Country of Origin
🇦🇺 Australia

Page Count
25 pages

Category
Quantitative Finance:
Risk Management