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Governments around the world use machine learning in automated decision-making systems for a broad range of functions. This book seeks to answer the question: what standards should be applied to machine learning to mitigate disparate impact in automated decision-making?
Natalie Heisler has advised public- and private-sector organizations around the world in the strategy and deployment of data, analytics, and artificial intelligence for more than twenty years. Natalie brings a unique, multidisciplinary perspective to her work, spanning social, regulatory, policy, and technical dimensions. Natalie has a BA in Psychology, an MSc in Mathematics, and an MA in Political Science and lives in Toronto, Canada.
Maura R. Grossman, JD, PhD, is a research professor in the David R. Cheriton School of Computer Science at the University of Waterloo and an affiliate faculty member at the Vector Institute of Artificial Intelligence, both in Ontario, Canada. She also is principal at Maura Grossman Law, in Buffalo, New York, USA. Professor Grossman's multidisciplinary work falls at the intersection of law, health, technology, ethics, and policy.
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