Artificial intelligence (“AI”) adoption in the insurance industry is increasing. One known risk as adoption of AI increases is the potential for unfair bias. Central to understanding where and how unfair bias may occur in AI systems is defining what unfair bias means and what constitutes fairness.
This research identifies methods to avoid or mitigate unfair bias unintentionally caused or exacerbated by the use of AI models and proposes a potential framework for insurance carriers to consider when looking to identify and reduce unfair bias in their AI models. The proposed approach includes five foundational principles as well as a four-part model development framework with five stage gates.Smith, L.T., E. Pirchalski, and I. Golbin. Avoiding Unfair Bias in Insurance Applications of AI Models. Society of Actuaries, August 2022.
Logan T. Smith, ASA
Publication Date: August 2022
Publication Site: SOA Research Institute