This video explores how actuaries can address AI bias through the lens of professional standards and ethical practice. It highlights key Actuarial Standards of Practice (ASOPs), including ASOP No. 56 on modeling and ASOP No. 23 on data quality, emphasizing how they guide decisions around data limitations, outliers, and bias sources. The video also covers the importance of continuing education on bias and presents a structured framework for evaluating bias in models through general, data, model, and socially-based questions. Practical examples illustrate how unchecked assumptions and systemic patterns can lead to unintended harm, reinforcing the need for critical inquiry and transparency in actuarial work.
Contributors: Yukki Yeung, FSA, MAAA; Sherry Chan, FSA, EA, MAAA, FCA; Jing Kai Ong, ASA; Jon Forster, ASA, MAAA