Model Governance and Explainable AI

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We are thrilled to host Nick Schmidt and Dr. Bryce Stephens of BLDS partners for an informed discussion about machine learning for high-impact and highly-regulated real-world applications. Our panelists will address policy, regulatory, and technical concerns regarding the use of AI for automated decision-making in areas like credit lending and employment. We'll also leave lots of time for audience questions. The discussion will be moderated by Patrick Hall of

Nick Schmidt, Director and Head of the AI/ML Innovation Practice, BLDS LLC
Dr. Bryce Stephens, Director, BLDS LLC
Patrick Hall, Senior Director of Product,

Nicholas Schmidt is a Partner and the A.I. Practice Leader at BLDS, LLC. In these roles, Nick specializes in the application of statistics and economics to questions of law, regulatory compliance, and best practices in model governance. His work involves developing techniques that allow his clients to make their A.I. models fairer and more inclusive. He has also helped his clients understand and implement methods that open “black-box” A.I. models, enabling a clearer understanding A.I.’s decision-making process.

Bryce Stephens provides economic research, econometric analysis, and compliance advisory services, with a specific focus on issues related to consumer financial protection, such as the Equal Credit Opportunity Act (ECOA), and emerging analytical methods.

Prior to joining BLDS, Dr. Stephens spent over seven years as an economist and Section Chief in the Office of Research at the Consumer Financial Protection Bureau. At the Bureau, he led a team of economists and analysts that conducted analysis and supported policy development on fair lending related supervisory exams, enforcement matters, rulemakings, and other policy initiatives.

Before joining the Bureau, Dr. Stephens served as an economic litigation consultant, conducting research and econometric analysis across of broad range of practice areas including: fair lending and consumer finance; labor, employment, and earnings; product liability; and healthcare.

Patrick Hall is senior director for data science products at where he focuses mainly on model interpretability and model management. Patrick is also currently an adjunct professor in the Department of Decision Sciences at George Washington University, where he teaches graduate classes in data mining and machine learning. Prior to joining, Patrick held global customer facing roles and research and development roles at SAS Institute.