Polytechnic University Milan Reports Findings in Philosophy (Fairness and Risk: An Ethical Argument for a Group Fairness Definition Insurers Can Use): Global Views – Philosophy

2023 OCT 06 (NewsRx) -- By a News Reporter-Staff News Editor at Politics, Law & Government Daily -- New research on Global Views - Philosophy is the subject of a report. According to news reporting originating from Milan, Italy, by NewsRx correspondents, research stated, “Algorithmic predictions are promising for insurance companies to develop personalized risk models for determining premiums. In this context, issues of fairness, discrimination, and social injustice might arise: Algorithms for estimating the risk based on personal data may be biased towards specific social groups, leading to systematic disadvantages for those groups.”

Funders for this research include Innosuisse - Schweizerische Agentur fur Innovationsforderung, HORIZON EUROPE Marie Sklodowska-Curie Actions, Schweizerischer Nationalfonds zur Forderung der Wissenschaftlichen Forschung.

Our news editors obtained a quote from the research from Polytechnic University Milan, “Personalized premiums may thus lead to discrimination and social injustice. It is well known from many application fields that such biases occur frequently and naturally when prediction models are applied to people unless special efforts are made to avoid them. Insurance is no exception. In this paper, we provide a thorough analysis of algorithmic fairness in the case of insurance premiums. We ask what ‘fairness’ might mean in this context and how the fairness of a premium system can be measured. For this, we apply the established fairness frameworks of the fair machine learning literature to the case of insurance premiums and show which of the existing fairness criteria can be applied to assess the fairness of insurance premiums. We argue that two of the often-discussed group fairness criteria, (also called or ) and (also known as ), are not normatively appropriate for insurance premiums. Instead, we propose the criterion (also known as ) as a morally defensible alternative that allows us to test for systematic biases in premiums towards certain groups based on the risk they bring to the pool. In addition, we clarify the connection between group fairness and different degrees of personalization.”

According to the news editors, the research concluded: “Our findings enable insurers to assess the fairness properties of their risk models, helping them avoid reputation damage resulting from potentially unfair and discriminatory premium systems.”

This research has been peer-reviewed.

For more information on this research see: Fairness and Risk: An Ethical Argument for a Group Fairness Definition Insurers Can Use. Philosophy & Technology, 2023;36(3):45.

The news editors report that additional information may be obtained by contacting Michele Loi, Dept. of Mathematics, Politecnico Di Milano, Milan, Italy.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1007/s13347-023-00624-9. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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