Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2018

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.

Keywords

Wages, Amazon Mechanical Turk, automation, survey

Discipline

Benefits and Compensation | Databases and Information Systems | Technology and Innovation

Research Areas

Data Science and Engineering

Publication

Proceedings of the 6th AAAI Conference on Human Computation and Crowdsourcing HCOMP 2018: Zürich, Switzerland, July 5-8

First Page

70

Last Page

78

Publisher

AAAI Press

City or Country

Palo Alto, CA

Copyright Owner and License

Publisher

Additional URL

https://www.aaai.org/ocs/index.php/HCOMP/HCOMP18/paper/viewFile/17920/16911

Download

Share

COinS