288 citations · 309 across the 3 of their papers we have counts for
4 papers
Selection Problems in the Presence of Implicit Bias
Jon Kleinberg, Manish Raghavan
Over the past two decades, the notion of implicit bias has come to serve as an important component in our understanding of discrimination in activities such as hiring, promotion, a…
On Fairness and Calibration
Geoff Pleiss, Manish Raghavan, Felix Wu +2
The machine learning community has become increasingly concerned with the potential for bias and discrimination in predictive models. This has motivated a growing line of work on w…
Planning with Multiple Biases
Jon Kleinberg, Sigal Oren, Manish Raghavan
Recent work has considered theoretical models for the behavior of agents with specific behavioral biases: rather than making decisions that optimize a given payoff function, the ag…
Planning Problems for Sophisticated Agents with Present Bias
Jon Kleinberg, Sigal Oren, Manish Raghavan
Present bias, the tendency to weigh costs and benefits incurred in the present too heavily, is one of the most widespread human behavioral biases. It has also been the subject of e…