Melting contestation: insurance fairness and machine learning

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



Cite this blog post
Arthur Charpentier (2023, December 14). Melting contestation: insurance fairness and machine learning. Freakonometrics. Retrieved February 26, 2024, from https://doi.org/10.58079/ovnh

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