Lecture and Laureate Dialogue: Analyzing Bias in Machine-Learning Algorithms/Hardening Algorithms against Biases

Jon Kleinberg, Yoshua Bengio

Talk Jon Kleinberg: Analyzing Bias in Machine-Learning Algorithms

Recent discussion in the public sphere has explored some of the way in which prediction algorithms trained on data might exhibit bias in their decision-making. This discussion, drawing on input from a wide range of communities, has involved a number of crucial trade-offs that can be formulated in precise terms. We will survey some of these trade-offs, including tensions between the simplicity of a classification rule and its equity guarantees, and tensions between competing definitions of what it means for a prediction algorithm to be fair to different groups. The talk will be based on joint work with Jens Ludwig, Sendhil Mullainathan, Manish Raghavan, and Cass Sunstein.

Laureate Discussion Yoshua Bengio and Jon Kleinberg: Hardening Algorithms against Biases