If we want to get fair outcomes, then we need to build fairness into algorithms.
Whether you’re looking for a job, a house, or a romantic partner, there’s an app for that. But as people increasingly turn to digital platforms in search of opportunity, Daniela Saban says it’s time we took a critical look at the role of algorithms, the invisible matchmakers operating behind our screens.
Saban is an Associate Professor of Operations, Information & Technology at Stanford Graduate School of Business whose research interests lie at the intersection of operations, economics, and computer science. With algorithms significantly influencing who gets matched with opportunities, she advocates for building “equity into the algorithm.”
In this episode of If/Then: Business, Leadership, Society, Saban explores how properly designed algorithms can improve the fairness and effectiveness of matching processes. If we want algorithms to work for good, then we need to make conscious choices about how we design them.
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If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society. Each episode features an interview with a Stanford GSB faculty member.
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