Published:
2018-07-09
Proceedings:
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 6
Volume
Issue:
Vol. 6 (2018): Sixth AAAI Conference on Human Computation and Crowdsourcing
Track:
Technical Papers
Downloads:
Abstract:
Earning money is a primary motivation for workers on Amazon Mechanical Turk, but earning a good wage is difficult because work that pays well is not easily identified and can be time-consuming to find. We explored the strategies that both low- and high-earning workers use to find and complete tasks via a survey of 360 workers. Nearly all workers surveyed had earning money as their primary goal, and workers used many of the same tools (browser extensions and scripts) and strategies in an attempt to earn more money, regardless of earning level. However, high-earning workers used more tools, were more involved in worker communities, and more heavily used batch completion strategies. A natural next step is to use automated systems to assist workers with finding and completing tasks. Workers found this idea interesting, but expressed concerns about impact on the quality of their work and whether using automated tools to support them would violate platform rules. We conclude with ideas for future work in supporting workers to earn more and design considerations for such tools.
DOI:
10.1609/hcomp.v6i1.13327
HCOMP
Vol. 6 (2018): Sixth AAAI Conference on Human Computation and Crowdsourcing
ISBN 978-1-57735-799-5