Algorithms inform the news you read, the TV shows you watch, and the advertisements that appear on your internet searches – and they also have a say in who gets a bank loan, what medical procedures are covered by insurance, and who gets selected for a job interview. As algorithms are used to make these decisions, how do we make sure they’re fair? And what does fairness even mean?

In this episode of Stanford Engineering’s The Future of Everything, computer science professor Omer Reingold explains how we can create definitions of fairness that can be incorporated into computer algorithms. Reingold and host, bioengineer Russ Altman, also discuss how flawed historic data may result in algorithms making unfair decisions and how a technique called multi-group fairness can improve health predictions for individuals. Listen and subscribe here.

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