A data-driven analysis of workers' earnings on Amazon Mechanical Turk

• Main Authors: HARA, Kotaro, ADAMS, Abigail, MILLAND, Kristy, SAVAGE, Saiph, CALLISON-BURCH, Chris, BIGHAM, Jeffrey P.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Crowdsourcing; Amazon Mechanical Turk; Hourly wage; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/4209; https://ink.library.smu.edu.sg/context/sis_research/article/5212/viewcontent/Hara_AData_DrivenAnalysisOfWorkersEearningsOnAmazonMechanicalTurk_CHI2018.pdf
• Institution: Singapore Management University

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/h, and only 4% earned more than $7.25/h. While the average requester pays more than $11/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.