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The Logic of Strategic Assets: From Oil to Artificial Intelligence

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  • Jeffrey Ding
  • Allan Dafoe

Abstract

What resources and technologies are strategic? This question is often the focus of policy and theoretical debates, where the label "strategic" designates those assets that warrant the attention of the highest levels of the state. But these conversations are plagued by analytical confusion, flawed heuristics, and the rhetorical use of "strategic" to advance particular agendas. We aim to improve these conversations through conceptual clarification, introducing a theory based on important rivalrous externalities for which socially optimal behavior will not be produced alone by markets or individual national security entities. We distill and theorize the most important three forms of these externalities, which involve cumulative-, infrastructure-, and dependency-strategic logics. We then employ these logics to clarify three important cases: the Avon 2 engine in the 1950s, the U.S.-Japan technology rivalry in the late 1980s, and contemporary conversations about artificial intelligence.

Suggested Citation

  • Jeffrey Ding & Allan Dafoe, 2020. "The Logic of Strategic Assets: From Oil to Artificial Intelligence," Papers 2001.03246, arXiv.org, revised May 2021.
  • Handle: RePEc:arx:papers:2001.03246
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    References listed on IDEAS

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    Cited by:

    1. Bofinger, Peter & Geißendörfer, Lisa & Haas, Thomas & Mayer, Fabian, 2023. "Credit as an instrument for growth: A monetary explanation of the Chinese growth story," W.E.P. - Würzburg Economic Papers 107, University of Würzburg, Department of Economics.
    2. Simone Vannuccini, 2025. "Move fast and integrate things: The making of a European Industrial Policy for Artificial Intelligence," MIOIR Working Paper Series 2025-02, The Manchester Institute of Innovation Research (MIoIR), The University of Manchester.
    3. Ludovic Dibiaggio & Lionel Nesta & Simone Vannuccini, 2024. "European Sovereignty in Artificial Intelligence: A Competence-Based Perspective," Working Papers hal-04841182, HAL.
    4. Lilia Patrignani & Michele Savini Zangrandi & Alessandro Schiavone, 2025. "Between sanctions and subsidies: reshaping the semiconductor ecosystem," Questioni di Economia e Finanza (Occasional Papers) 934, Bank of Italy, Economic Research and International Relations Area.
    5. Markus Bruckner & Chadi Bou Habib & Martin Lokanc, 2023. "Natural Resources, State Ownership, and Economic Development," ANU Working Papers in Economics and Econometrics 2023-694, Australian National University, College of Business and Economics, School of Economics.
    6. Ding, Jeffrey, 2022. "Techno-industrial Policy for New Infrastructure: China’s Approach to Promoting Artificial Intelligence as a General Purpose Technology," Institute on Global Conflict and Cooperation, Working Paper Series qt1sb844ws, Institute on Global Conflict and Cooperation, University of California.
    7. Nora von Ingersleben‐Seip, 2023. "Competition and cooperation in artificial intelligence standard setting: Explaining emergent patterns," Review of Policy Research, Policy Studies Organization, vol. 40(5), pages 781-810, September.
    8. Pedro Jácome de Moura & Carlos Denner Santos Junior & Carlo Gabriel Porto-Bellini & José Jorge Lima Dias Junior, 2024. "The Over-Concentration of Innovation and Firm-Specific Knowledge in the Artificial Intelligence Industry," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(4), pages 20547-20577, December.

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