The growing footprint of AI has led some to trumpet the technology as one that could advance society, while raising fears about what that future could bring. Whether it’s considering the implications of regulating the technology or AI’s effect in health care and other industries, the Academy is delving into this important issue.
- Discrimination Considerations for AI Learning (issue brief)
- Using AI to Test AI (article)
- Regulating AI (article)
- AI Health Care Pros and Cons (article)
- AI’s Effect on Actuarial Work (article)
Back to the Issues Clearinghouse
Discrimination: Considerations for Machine Learning, AI Models, and Underlying Data
Algorithmic predictions are promising for insurance companies to develop personalized risk models when engaged in insurance pricing and underwriting. In this context, issues of fairness, discrimination, and social injustice might arise. As the use of predictive models and similar automated tools increases, there has been enhanced regulatory scrutiny around the effectiveness of modern techniques to safeguard against discriminatory outcomes that exacerbate preexisting social and economic inequalities. During this webinar, our speakers—members of the Academy’s Data Science and Analytics Committee—discussed discrimination in insurance and present practical methods for testing and monitoring of algorithms to address regulatory and societal concerns.