Authors
Toni Kaplan, Susumu Saito, Kotaro Hara, and Jeffrey P. Bigham
Publication
AAAI Publications, Sixth AAAI Conference on Human Computation and Crowdsourcing
Abstract
Earning money is a primary motivation for workers on Amazon Mechanical Turk, but earning a good wage is difļ¬cult because work that pays well is not easily identiļ¬ed and can be time-consuming to ļ¬nd. We explored the strategies that both low- and high-earning workers use to ļ¬nd 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 ļ¬nding 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.