Discrimination: Considerations for Machine Learning, AI Models, and Underlying Data
May 2, 2024 | Noon to 1:30 p.m. EDT | USQS Bias CE Available 

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ABOUT THIS WEBINAR
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.

SPEAKERS

• Jennifer Balester, MAAA, FCAS
  Member, Data Science and Analytics Committee
• Kirsten Pedersen, MAAA, FSA         
  Member, Data Science and Analytics Committee
• Andrea Rome, MAAA, FSA
  Member, Data Science and Analytics Committee

CONTINUING EDUCATION

The American Academy of Actuaries believes in good faith that attendance at this live webinar constitutes an organized activity as defined under the current Qualification Standards for Actuaries Issuing Statements of Actuarial Opinion in the United States, and that attendees may earn up to 1.8 bias continuing education (CE) credits for attending this live webinar.

QUESTIONS

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