Data & Society > our work > paper > Discriminating Tastes: Customer Ratings as Vehicles for Bias

paper | 10.19.16

Discriminating Tastes: Customer Ratings as Vehicles for Bias

Alex Rosenblat, Karen Levy, Solon Barocas, Tim Hwang


Credit: Alexandra Mateescu


D&S researchers Alex Rosenblat and Tim Hwang and D&S affiliates Solon Barocas and Karen Levy examine how bias may creep into evaluations of Uber drivers through consumer-sourced rating systems:

Through the rating system, consumers can directly assert their preferences and their biases in ways that companies are prohibited from doing on their behalf. The fact that customers may be racist, for example, does not license a company to consciously or even implicitly consider race in its hiring decisions. The problem here is that Uber can cater to racists, for example, without ever having to consider race, and so never engage in behavior that amounts to disparate treatment. In effect, companies may be able to perpetuate bias without being liable for it.”

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