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 language | English |
|---|---|
| Title of host publication | HCOMP 2020 - Proceedings of the 8th AAAI Conference on Human Computation and Crowdsourcing |
| Editors | Lora Aroyo, Elena Simperl |
| Publisher | Association for the Advancement of Artificial Intelligence |
| Pages | 155-158 |
| Number of pages | 4 |
| ISBN (Print) | 9781577358480 |
| DOIs | |
| State | Published - 2020 |
| Externally published | Yes |
| Event | 8th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2020 - Virtual, Online Duration: 25 10 2020 → 29 10 2020 |
Publication series
| Name | Proceedings of the AAAI Conference on Human Computation and Crowdsourcing |
|---|---|
| Volume | 8 |
| ISSN (Print) | 2769-1330 |
| ISSN (Electronic) | 2769-1349 |
Conference
| Conference | 8th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2020 |
|---|---|
| City | Virtual, Online |
| Period | 25/10/20 → 29/10/20 |
Bibliographical note
Publisher Copyright:© 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
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