Abstract
Despite the benefits of team diversity, individuals often choose to work with similar others. Online team formation systems have the potential to help people assemble diverse teams. Systems can connect people to collaborators outside their networks, and features can quantify and raise the salience of diversity to users as they search for prospective teammates. But if we build a feature indicating diversity into the tool, how will people react to it? Two experiments manipulating the presence or absence of a "diversity score" feature within a teammate recommender demonstrate that, when present, individuals avoid collaborators who would increase team diversity in favor of those who lower team diversity. These results have important practical implications. Though the increased access to diverse teammates provided by recommender systems may benefit diversity, designers are cautioned against creating features that raise the salience of diversity as this information may undermine diversity.
Original language | English (US) |
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Title of host publication | CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems |
Publisher | Association for Computing Machinery |
ISBN (Electronic) | 9781450367080 |
DOIs | |
State | Published - Apr 21 2020 |
Event | 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020 - Honolulu, United States Duration: Apr 25 2020 → Apr 30 2020 |
Publication series
Name | Conference on Human Factors in Computing Systems - Proceedings |
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Conference
Conference | 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020 |
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Country/Territory | United States |
City | Honolulu |
Period | 4/25/20 → 4/30/20 |
Funding
This material is based upon work supported by the National Aeronautics and Space Administration under grant NNX15AM32G, and the National Institutes of Health under award number R01GM112938-01. We thank Sabine Brunswicker, Silvia Andreoli, Julia de Souza Faria, and the CITEP Lab from Universidad de Buenos Aires for helping us in conducting these experiments. We also thank the anonymous reviewers for their feedback and suggestions.
Keywords
- diversity
- mixed-effect logistic regressions
- social recommenders
- team formation
- teams
ASJC Scopus subject areas
- Software
- Human-Computer Interaction
- Computer Graphics and Computer-Aided Design