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Fighting bias with bias: How same-race endorsements reduce racial discrimination on Airbnb.

Minsu ParkChao YuMichael W Macy
Published in: Science advances (2023)
Recent studies have documented racial discrimination in online interactions, mirroring the historic bias observed offline. The sharing economy is especially vulnerable due to greater dependence on mutual trust in sharing a ride, residence, or date with a stranger. These services rely on user recommendations to build trust, but the effects of these peer evaluations on racial bias are only beginning to be explored. Using data from Airbnb, we examine in-group preference for same-race hosts as well as same-race recommendations. The unexpected result is that these two manifestations of racial bias are offsetting, not reinforcing. White guests largely overcame their racial bias in host selection when hosts were endorsed by previous white guests. Moreover, we found no evidence of racial bias in the affective enthusiasm of endorsements, which suggests that the preference for same-race endorsements is motivated by the race of the recommender, not the content of the recommendation.
Keyphrases
  • health information
  • african american
  • social media
  • mental health
  • machine learning
  • artificial intelligence
  • health insurance