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Does Exposure to Diverse Perspectives Mitigate Biases in Crowd work? An Explorative Study

  • Purdue University
  • Washington University St. Louis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

Earlier research has shown the promise of enabling worker interactions in crowd work to mitigate worker biases and improve the quality of crowd work. In this study, we focus on one characteristic of the interacting workers that may influence the effectiveness of worker interactions in enhancing crowd work—the diversity of perspectives that the interacting workers bring together—and we explore whether and how interactions between a set of workers holding different perspectives can help mitigate biases in crowd work. Through two sets of randomized experiments, we find that whether interactions between workers with different perspectives can help mitigate biases in crowd work depends on task properties. We also find no conclusive evidence in our experimental settings suggesting that interactions among workers with diverse perspectives reduce biases in crowd work to a larger extent compared to interactions among workers with similar perspectives.

Original languageEnglish
Title of host publicationHCOMP 2020 - Proceedings of the 8th AAAI Conference on Human Computation and Crowdsourcing
Editors Lora Aroyo, Elena Simperl
PublisherAssociation for the Advancement of Artificial Intelligence
Pages155-158
Number of pages4
ISBN (Print)9781577358480
DOIs
StatePublished - 2020
Externally publishedYes
Event8th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2020 - Virtual, Online
Duration: 25 10 202029 10 2020

Publication series

NameProceedings of the AAAI Conference on Human Computation and Crowdsourcing
Volume8
ISSN (Print)2769-1330
ISSN (Electronic)2769-1349

Conference

Conference8th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2020
CityVirtual, Online
Period25/10/2029/10/20

Bibliographical note

Publisher Copyright:
© 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

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