Explainable AI as a Tool for Risk Managers
Thought Leadership Webinar: Improvements to machine learning (ML) technology are presenting organizations with higher promise coupled with greater risk, with one of the greatest sources of risk being reliance on black box techniques. This webinar explains the value to risk managers of using "explainable AI" to manage black box risk.
Date:
May 11, 2022
Time:
10:00 - 11:00 a.m. EDT
3:00 - 4:00 p.m. BST
Presented By:
Hersh Shefrin, Ph.D.
Mario L. Belotti Professor of Finance,
Santa Clara University
Session Length:
60 minutes
Risk management teams who focus on risks associated with artificial intelligence (AI) are either including at least one AI validator, meaning a team member having a background in data science, or are relying on consultants and external validators. They are doing so to manage the risk associated with biased outcomes being produced by machine learning (ML)-generated algorithms. This risk is compounded by the fact that ML-techniques, by their nature, are black box in nature.
Data scientists have been responding to issues of algorithmic bias in several ways, including developing tools for explainable AI which seek to shed light on the inner workings of ML-generated algorithms. Explainable AI is a relatively new approach which analyzes ML-generated decision models and produces output which can serve as documentation for various constituencies, including regulatory bodies.
Key takeaways relate to using explainable AI to identify the relative importance which ML-algorithms attach to different features, along with risks related to misjudgments and bias that stem from the use of these algorithms, and for that matter from explainable AI as well.
| About Our Expert |
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Hersh Shefrin is the Mario L. Belotti Professor of Finance at Santa Clara University. He is one of the pioneers in the behavioral approach to economics and finance. Together with Nobel laureate Richard Thaler, he developed an economic theory of self-control. The January 2001 issue of CFO magazine lists him among the academic stars of finance. A 2003 article in the American Economic Review listed him as one of the top fifteen economic theorists to have influenced empirical work.
Professor Shefrin is the author of seven books and numerous articles about how behavioral ideas impact real world decisions. In 2009, his book Beyond Greed and Fear was recognized by J.P. Morgan Chase as one of the top ten books published since 2000.
Professor Shefrin received his B.Sc. (Hons.) degree from the University of Manitoba, an M.Math degree from the University of Waterloo, and his Ph.D. from the London School of Economics. He also holds an honorary doctorate from the University of Oulu, Finland. He is frequently interviewed by the press and his work was profiled by BBC-TV in February 2014. He writes a monthly blog post for Forbes, and has intermittently written for The Wall Street Journal, The Huffington Post, and VOX. His Twitter handle is @HershShefrin.
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| Continued Risk Learning Credits: 1 |
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Members (Sustaining, Corporate, RIM & Contributing)
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COMPLIMENTARY |
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Non Member |
$30 USD
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