Nice review of our paper , with Laurence Barry, on montrealethics.ai,
Machine learning tends to replace the actuary in the selection of features and the building of pricing models. However, avoiding subjective judgments thanks to automation does not necessarily mean that biases are removed. Nor does the absence of bias warrant fairness. This paper critically analyzes discrimination and insurance fairness with machine learning.
Melting contestation: insurance fairness and machine learning
OpenEdition suggests that you cite this post as follows:
Arthur Charpentier (December 14, 2023). Melting contestation: insurance fairness and machine learning. Freakonometrics. Retrieved April 22, 2025 from https://doi.org/10.58079/ovnh