Data Challenges in Building a Facial Recognition Model and How to Mitigate Them

Author

Victoria Zhang, FSA, FCIA

Description

This paper is an introduction to AI technology designed for actuaries to understand how the technology works, the potential risks it could introduce, and how to mitigate risks. The author focuses on data bias as it is one of the main concerns of facial recognition technology. This research project was jointly sponsored by the Diversity Equity and Inclusion Research and the Actuarial Innovation and Technology Strategic Research Programs

Report

Data Challenges in Building a Facial Recognition Model and How to Mitigate Them

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Data Challenges in Building a Facial Recognition Model and How to Mitigate Them

Acknowledgments

The SOA Research Institute would like to thank the following members of the Project Oversight Group for their thoughtful guidance and diligent review throughout the development of this research:

Ann Weber, JD
Nick Gabriele, FSA, MAAA
Noel Harewood, FSA, MAAA
Mengting Kim, FSA, CERA, MAAA
Hezhong (Mark) Ma, FSA, MAAA
Mark Sayre, FSA, CERA
Shisheng (Rose) Qian, ASA, CERA

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