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  1.  16
    Personalization as a promise: Can Big Data change the practice of insurance?Arthur Charpentier & Laurence Barry - 2020 - Big Data and Society 7 (1).
    The aim of this article is to assess the impact of Big Data technologies for insurance ratemaking, with a special focus on motor products.The first part shows how statistics and insurance mechanisms adopted the same aggregate viewpoint. It made visible regularities that were invisible at the individual level, further supporting the classificatory approach of insurance and the assumption that all members of a class are identical risks. The second part focuses on the reversal of perspective currently occurring in data analysis (...)
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  2.  28
    Fairness in Uncertainty: Some Limits and Misinterpretations of Actuarial Fairness.Sylvestre Frezal & Laurence Barry - 2020 - Journal of Business Ethics 167 (1):127-136.
    The recent proliferation of new data and technologies enables increasingly finer personalization of products and prices in every domain. In insurance, this revives and enlarges old debates around fairness that have never been completely settled. We will argue that the commonly accepted “actuarial fairness” as based on the “individual cost of risk” derives in fact from a conflation: while it indicates the average cost for a group of insureds from the perspective of an insurance company—and is therefore sound from a (...)
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  3.  10
    Epidemic and Insurance: Two Forms of Solidarity.Laurence Barry - 2022 - Theory, Culture and Society 39 (7-8):217-235.
    Despite their common core in statistics, insurance and epidemiology propel two different forms of solidarity. In insurance, the collective is a source of protection, thanks to the pooling of risks; in epidemics by contrast, the group remains the source of danger for the individual. The aim of this paper is to highlight the conceptions of community and solidarity at play in epidemics in contradistinction to insurance, with a focus on the shift introduced by big data and algorithms. Paradoxically, while the (...)
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  4.  13
    The rationality of the digital governmentality.Laurence Barry - 2019 - Journal for Cultural Research 23 (4):365-380.
    While it is often claimed that the emerging digital governmentality functions as a new apparatus of surveillance, the aim of this paper is to characterise this regime in relation to Foucault’s disc...
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  5.  15
    Melting contestation: insurance fairness and machine learning.Laurence Barry & Arthur Charpentier - 2023 - Ethics and Information Technology 25 (4):1-13.
    With their intensive use of data to classify and price risk, insurers have often been confronted with data-related issues of fairness and discrimination. This paper provides a comparative review of discrimination issues raised by traditional statistics versus machine learning in the context of insurance. We first examine historical contestations of insurance classification, showing that it was organized along three types of bias: pure stereotypes, non-causal correlations, or causal effects that a society chooses to protect against, are thus the main sources (...)
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  6.  13
    Modernity’s exclusions.Laurence Barry - 2024 - Contemporary Political Theory 23 (1):146-151.
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