Towards fair and pro-social employment of digital pieceworkers for sourcing machine learning training data
Author:
Affiliation:
1. Georgia Institute of Technology, United States
2. DataWorks, United States
3. Learning Sciences, Georgia State University, United States
4. School of Interactive Computing, Georgia Institute of Technology, United States
Funder
Constellations Center for Equity in Computing at Georgia Tech
Georgia Tech College of Computing
National Science Foundation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3491101.3516384
Reference54 articles.
1. To Live in Their Utopia: Why Algorithmic Systems Create Absurd Outcomes
2. Examining Crowd Work and Gig Work Through The Historical Lens of Piecework
3. Daniel Archambault Helen Purchase and Tobias Hoßfeld (eds.). 2017. Evaluation in the Crowd. Crowdsourcing and Human-Centered Experiments: Dagstuhl Seminar 15481 Dagstuhl Castle Germany November 22 – 27 2015 Revised Contributions. Springer International Publishing Cham. https://doi.org/10.1007/978-3-319-66435-4 Daniel Archambault Helen Purchase and Tobias Hoßfeld (eds.). 2017. Evaluation in the Crowd. Crowdsourcing and Human-Centered Experiments: Dagstuhl Seminar 15481 Dagstuhl Castle Germany November 22 – 27 2015 Revised Contributions. Springer International Publishing Cham. https://doi.org/10.1007/978-3-319-66435-4
4. Exploring the Quality, Efficiency, and Representative Nature of Responses Across Multiple Survey Panels
5. Work experiences on MTurk: Job satisfaction, turnover, and information sharing
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