Reducing Prejudice against Muslim Americans: Using an Online Panel to Evaluate Two De-Biasing Interventions

While there is evidence regarding discrimination against Muslims, few studies focus on reducing it. Research from behavioral economics, psychology, and political science suggests that conversation-based interventions may reduce prejudice against out-groups, at least in the short term. Economist Yan Chen, political scientist Ann Lin, and computer scientist Kentaro Toyama will analyze and compare the effects of two conversation-based interventions in a randomized online experiment, using a representative sample of the U.S. population. The first focused on perspective-taking, where participants have short conversations about their own experiences of discrimination. The second, focused on value-consistency, had participants writing about positive moral values. These interventions both require “active processing,” which can have lasting effects in reducing bias. The PIs will examine the degree to which short value-consistency and perspective-taking conversations decrease anti-Muslim bias. These results will complement those from an earlier RSF grant, where researchers went door to door to administer these interventions in the Detroit metro area. The online interventions seek to confirm or enhance the original findings with a representative sample, and to determine whether online interventions work as well as face-to-face conversations.