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
Abstract
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 http://creativecommons.org/licenses/by/4.0/. |
| 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: |
Preview
Available under License Creative Commons: Attribution International Public License 4.0.
Download (273kB) | Preview
Export
Downloads
Downloads per month over past year
Metadata
Metadata
MetadataAltmetric
CORE (COnnecting REpositories)
Actions (login required)
Actions (login required)
Admin Login