AI Safety and Competition

Jay Pil Choi, Doh-Shin Jeon and Domenico Menicucci

No 26-1745, TSE Working Papers from Toulouse School of Economics (TSE)

Abstract: This paper examines how competition affects the timing of AI deployment under safety risk. We show that competition can generate two distortions relative to joint–profit maximization: a race to the bottom and insufficient entry. A race to the bottom arises when first-mover advantages induce premature deployment and is more likely as technological correlation (homogenization) increases. Conversely, firms may delay entry to free-ride on rivals’ experimentation, leading to insufficient entry. Even when private incentives under joint–profit maximization are aligned with social incentives, competition can still induce socially inefficient early deployment. We discuss policy implications for improving deployment timing.

Keywords: AI; Competition; Optimal Deployment Time; Race to the Bottom. (search for similar items in EconPapers)
JEL-codes: D4 L1 L5 (search for similar items in EconPapers)
Date: 2026-05-07
New Economics Papers: this item is included in nep-com and nep-mic
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Persistent link: https://EconPapers.repec.org/RePEc:tse:wpaper:131711

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