By: Ming Yin, Mary L. Gray, Siddharth Suri, Jennifer Wortman Vaughan
Since its inception, crowdsourcing has been considered a black-box approach to solicit labor from a crowd of workers. Prior work has shown the existence of edges between workers. We build on and extend this discovery by mapping the entire communication network of workers on Amazon Mechanical Turk, a leading crowdsourcing platform. We execute a task in which over 10,000 workers from across the globe self-report their communication links to other workers,thereby mapping the communication network among workers. Our results suggest that while a large percentage of workers indeed appear to be independent, there is a rich network topology over the rest of the population. That is, there is a substantial communication network within the crowd. We further examine how online forum usage relates to network topology, how workers communicate with each other via this network, how workers’ experience levels relate to their network positions, and how U.S. workers difer from international workers in their network characteristics. We conclude by discussing the implications of our findings for requesters, workers, and platform providers like Amazon.
By: Sara Constance Kingsley, Mary L. Gray and Siddharth Suri (2015)
Amazon Mechanical Turk (AMT) is an online labor market that defines itself as “a marketplace for work that requires human intelligence.” Early advocates and developers of crowdsourcing platforms argued that crowdsourcing tasks are designed so people of any skill level can do this labor online. However, as the popularity of crowdsourcing work has grown, the crowdsourcing literature has identified a peculiar issue: that work quality of workers is not responsive to changes in price. This means that unlike what economic theory would predict, paying crowdworkers higher wages does not lead to higher quality work. This has led some to believe that platforms, like AMT, attract poor quality workers. This article examines different market dynamics that might, unwittingly, contribute to the inefficiencies in the market that generate poor work quality. We argue that the cultural logics and socioeconomic values embedded in AMT’s platform design generate a greater amount of market power for requesters (those posting tasks) than for individuals doing tasks for pay (crowdworkers). We attribute the uneven distribution of market power among participants to labor market frictions, primarily characterized by uncompetitive wage posting and incomplete information. Finally, recommendations are made for how to tackle these frictions when contemplating the design of an online labor market.
By: Mary L. Gray, Siddharth Suri, Syed Shoaib Ali, and Deepti Kulkarni (2016)
Abstract: The main goal of this paper is to show that crowdworkers collaborate to fulfill technical and social needs left by the platform they work on. That is, crowdworkers are not the independent, autonomous workers they are often assumed to be, but instead work within a social network of other crowdworkers. Crowdworkers collaborate with members of their networks to 1) manage the administrative overhead associated with crowdwork, 2) find lucrative tasks and reputable employers and 3) recreate the social connections and support often associated with brick and mortar-work environments. Our evidence combines ethnography, interviews, survey data and larger scale data analysis from four crowdsourcing platforms, emphasizing the qualitative data from the Amazon Mechanical Turk (MTurk) platform and Microsoft’s proprietary crowdsourcing platform, the Universal Human Relevance System (UHRS). This paper draws from an ongoing, longitudinal study of crowdwork that uses a mixed methods approach to understand the cultural meaning, political implications, and ethical demands of crowdsourcing.
The Pacific Standard, Aug 21st, 2015: The Future of Work: Caring for the Crowdworker going it alone –> By Mary Gray
“Crowdwork represents a small but growing microclimate in the ecosystem known as platform economies. These are business activities burgeoning through the ties that bind the Internet, smartphone apps, and social networks. The boss here is not a mid-level manager but an application programming interface or API deployed on a platform. The platform—owned and operated by companies like Amazon, Upwork (formerly oDesk), and LeadGenius—works in concert with an API to generate and verify workers’ accounts, handle the workflow of millions of online job postings, and route payments to workers once they complete their tasks and submit them for approval from an invisible, ethereal “employer.”
Bloomberg News, Aug 12, 2015: Fixing the chaotic crowdworker economy –> By Mary Gray
From our surveys of thousands of such workers, we know a lot of them string together 30 to 50 hours of work a week, earning a couple of cents to a few dollars per task. They rely on workers’ forums to share information about how to sign up for platforms, what jobs to consider, which “task creators” to avoid, and even how to do certain jobs when the instructions leave out key details.
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