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Opening up the black box: Technological transparency and prevention

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  • Lu Li

Abstract

We discuss the behavioral and welfare implications of uncovering determinants of successful prevention. Based on a novel reinterpretation of prevention, we introduce the concept of technological transparency (TT)—the extent to which scientific knowledge allows agents to predict the success of their effort conditional on observable risk determinants. When risk determinants are observable ex ante, TT refines the information partition and induces more efficient prevention but does not necessarily improve welfare when the risk is insurable. At the same time, TT may harm welfare if information is incompletely disclosed. When risk determinants are only observable ex post, TT may increase effort by triggering future regret. Our framework facilitates a deeper understanding of the connection between knowledge and the efficient choice of preventive effort. Our findings inform the cost‐benefit analysis of advancing knowledge about risk processes, as well as the effective disclosure of such knowledge to the public.

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  • Lu Li, 2021. "Opening up the black box: Technological transparency and prevention," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(3), pages 665-693, September.
    • Handle: RePEc:bla:jrinsu:v:88:y:2021:i:3:p:665-693
    DOI: 10.1111/jori.12328
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    Cited by:

    1. Martin Eling & Irina Gemmo & Danjela Guxha & Hato Schmeiser, 2024. "Big data, risk classification, and privacy in insurance markets," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 49(1), pages 75-126, March.
    2. Richard Peter, 2024. "The economics of self-protection," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 49(1), pages 6-35, March.

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