The platform belongs to those who work on it! Co-designing worker-centric task distribution models



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Rozas, David and Saldivar, Jorge and Zelickson, Eve (2021) The platform belongs to those who work on it! Co-designing worker-centric task distribution models. In 17th International Symposium on Open Collaboration (OpenSym 2021), 2021/09, Madrid. (In Press)

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Today, digital platforms are increasingly mediating our day-to-day work and crowdsourced forms of labour are progressively gaining importance (e.g. Amazon Mechanical Turk, Universal Human Relevance System, TaskRabbit). In many popular cases of crowdsourcing, a volatile, diverse, and globally distributed crowd of workers compete among themselves to find their next paid task. The logic behind the allocation of these tasks typically operates on a "First-Come, First-Served" basis. This logic generates a competitive dynamic in which workers are constantly forced to check for new tasks. This article draws on findings from ongoing collaborative research in which we co-design, with crowdsourcing workers, three alternative models of task allocation beyond "First-Come, First-Served", namely (1) round-robin, (2) reputation-based, and (3) content-based. We argue that these models could create fairer and more collaborative forms of crowd labour. We draw on Amara On Demand, a remuneration-based crowdsourcing platform for video subtitling and translation, as the case study for this research. Using a multi-modal qualitative approach that combines data from 10 months of participant observation, 25 semi-structured interviews, two focus groups, and documentary analysis, we observed and co-designed alternative forms of task allocation in Amara on Demand. The identified models help envision alternatives towards more worker-centric crowdsourcing platforms, understanding that platforms depend on their workers, and thus ultimately they should hold power within them.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:crowdsourcing, digital labour, distribution of value, future of work, human computation, platform economy, task allocation, workercentric platforms
Subjects:Sciences > Computer science > Computer networks
Sciences > Computer science > Software
Social sciences > Sociology
ID Code:67612
Deposited On:06 Sep 2021 13:28
Last Modified:06 Sep 2021 13:37

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