The Case for Resilience and Risk Management as Core Elements of Competitive National AI Strategy
Global artificial intelligence (AI) competition should be understood not just as a sprint to develop the most-advanced systems but also as a longer-term marathon to accumulate net benefits—the gains from AI minus the costs of accidents, misuse, and disruption. In that marathon, resilience and risk management could be powerful levers of strategic advantage, not merely responses to safety concerns.
In this paper, drawing on Charles Perrow’s theory of “normal accidents” in complex technological systems, the author demonstrates how firms and nations that are well prepared to navigate a world of recurring AI risk could outperform those that are not—including those that won the initial development sprint. Four intermediate scenarios explore how different levels of AI-risk cost could affect net benefits at the national and global levels and how even modest resilience advantages could compound into decisive competitive edges over time.
The author identifies policy options at every level—individuals, firms, infrastructure operators, and state, local, and national governments—for building the resilience needed to compete effectively in a world of normal AI accidents.
