Hidden Bias - Identifying Unintended Consequences in Machine Learning

Over the past few years there have been several examples of machine learning models with unintended bias in applications ranging from hiring to provisioning healthcare services. As these models become more prevalent, identifying potential sources of bias and how to address them will become increasingly important. This session will cover some of the factors that can contribute to hidden bias as well as potential methods for identifying them. It will also address the role of actuarial subject matter expertise in combating potential issues. At the conclusion of the session, attendees will be able to: - Identify potential sources of bias in machine learning models - Evaluate a model for potential bias - Explain how actuaries can help combat potential bias in models

Jason Altieri

Jason Altieri is a Senior Data Science Team Lead with Milliman PRM Analytics. Jason’s primary focus is on healthcare data transformation and population health analytics to support risk based contracting arrangements across multiple lines of business. Prior to joining Milliman in 2014, Jason worked in the banking industry assessing risk sensitivity models.

Mason Roberts

Mason focuses on supporting provider organizations address the challenges and opportunities presented by the current US healthcare shift to value-based reimbursement. His focus is on developing financially sustainable programs to improve care outcomes. These programs often address the underlying social determinants present in health system populations, reduce friction in health systems, and strategically maximize value-based contracts. Mason has been involved in projects focused on behavioral health and public health, including certifying rates for Behavioral Health Organizations, parity testing, and benchmarking. He has also performed considerable research in public health and how health systems have been impacted by payment reform models. Mason has assisted with the pricing and filing of individual and small group products for commercial health insurance plans. This work has included expansion application filings with additional solvency requests, pro forma financial development, market analysis, and benefit plan design. Previously Mason lived in Louisville, KY, where he started the non-profit Louisville Grows, which focuses on food security and environmental justice. He has also worked for city and county governments on economic development and labor contract negotiations. Mason received his Associateship in the Society of Actuaries in March 2017.

Holly Moore

Holly has been working as a consulting analyst at Milliman for 4 years. She works in a product group called PRM Analytics where her work involves engaging with clients and interacting with PRM’s machine learning based healthcare products.

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Webcast Session
08/25/2020 at 1:00 PM (EDT)  |  75 minutes
08/25/2020 at 1:00 PM (EDT)  |  75 minutes
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