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Fairness: plurality, causality, and insurability

Fahrenwaldt, M., Furrer, C., Hiabu, M. E. , Huang, F., Jørgensen, F. H., Lindholm, M., Loftus, J., Steffensen, M. & Tsanakas, A. ORCID: 0000-0003-4552-5532 (2024). Fairness: plurality, causality, and insurability. European Actuarial Journal, doi: 10.1007/s13385-024-00387-3


This article summarizes the main topics, findings, and avenues for future work from the workshop Fairness with a view towards insurance held August 2023 in Copenhagen, Denmark.

Publication Type: Article
Additional Information: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
Publisher Keywords: Artificial intelligence, Discrimination, Insurance, Machine learning
Subjects: H Social Sciences > HG Finance
Q Science > QA Mathematics
Departments: Bayes Business School
Bayes Business School > Actuarial Science & Insurance
SWORD Depositor:
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