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Levy, Barocas Earn Best Paper at Oxford Conference

Two of Info Sci's newest hires Karen Levy and Solon Barocas, working with two Data & Society colleagues, picked up Best Paper at Oxford's Internet, Policy & Politics Conference held in September. The team's paper, "Discriminating Tastes: Customer Ratings as Vehicles for Bias", examines how bias may creep into evaluations of Uber drivers through consumer-sourced rating systems.

An excerpt: “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.”