Conference item
A data-driven analysis of workers' earnings on Amazon Mechanical Turk
- Abstract:
- A growing number of people are working as part of on-line crowd work. Crowd work is often thought to be low wage work. However, we know little about the wage distribution in practice and what causes low/high earnings in this setting. We recorded 2,676 workers performing 3.8 million tasks on Amazon Mechanical Turk. Our task-level analysis revealed that workers earned a median hourly wage of only ~2 USD/h, and only 4% earned more than 7.25 USD/h. While the average requester pays more than 11 USD/h, lower-paying requesters post much more work. Our wage calculations are influenced by how unpaid work is accounted for, e.g., time spent searching for tasks, working on tasks that are rejected, and working on tasks that are ultimately not submitted. We further explore the characteristics of tasks and working patterns that yield higher hourly wages. Our analysis informs platform design and worker tools to create a more positive future for crowd work.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
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(Preview, Accepted manuscript, pdf, 1.4MB, Terms of use)
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- Publisher copy:
- 10.1145/3173574.3174023
Authors
- Publisher:
- Association for Computing Machinery
- Host title:
- ACM CHI Conference on Human Factors in Computing Systems (CHI 2018)
- Journal:
- ACM CHI Conference on Human Factors in Computing Systems More from this journal
- Publication date:
- 2018-04-21
- Acceptance date:
- 2017-12-21
- DOI:
- Keywords:
- Pubs id:
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pubs:817450
- UUID:
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uuid:9a415bec-5a69-447d-8c23-6b2aeef4de07
- Local pid:
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pubs:817450
- Source identifiers:
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817450
- Deposit date:
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2018-01-11
Terms of use
- Copyright holder:
- Adams et al
- Copyright date:
- 2018
- Notes:
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© 2018 Copyright is held by the owner/author(s). Publication rights
licensed to ACM. This is the accepted manuscript version of the article. The final version is available online from the Association for Computing Machinery at: http://dx.doi.org/10.1145/3173574.3174023
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