Bates, J. orcid.org/0000-0001-7266-8470, Checco, A. orcid.org/0000-0002-0981-3409 and Gerakopoulou, E. (2022) Worker perspectives on designs for a crowdwork co-operative. In: Hepp, A., Jarke, J. and Kramp, L., (eds.) New Perspectives in Critical Data Studies : The Ambivalences of Data Power. Palgrave Macmillan , pp. 415-443. ISBN 9783030961794
Abstract
Crowdwork platforms such as Amazon Mechanical Turk (AMT) are a crucial infrastructural component of our global data assemblage. Through these platforms, low-paid crowdworkers perform the vital labour of manually labelling large-scale and complex datasets, labels that are needed to train machine learning and AI models (Tubaro et al., Big Data & Society, 7(1), 2020) and which enable the functioning of much digital technology, from niche applications to global platforms such as Google, Amazon and Facebook.
In this chapter, we reflect on how a ‘design justice’ approach might be valuable to build on insights gained from a series of exploratory discussions we have engaged in with US-based crowdworkers about how a crowdworker co-operative might work in practice, and begin to sketch out a potential software architecture that could form the basis of future participative approaches to the design and development of a crowdworker co-operative.
We begin by describing and reflecting on our own evolving methodology and how it fits with the ‘design justice’ lens we propose for future work. Following this, we present findings from our discussions with crowdworkers about how a crowdwork co-operative might work in practice, including what values workers would like to see embedded in the design. We then finish with the outline of a prototype software architecture for a crowdworker co-operative that could be used as a starting point in future design work in collaboration with crowdworkers.
Metadata
Item Type: | Book Section |
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Copyright, Publisher and Additional Information: | © 2021 The Authors. Open Access: This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 Nov 2021 08:40 |
Last Modified: | 03 Aug 2022 10:28 |
Status: | Published |
Publisher: | Palgrave Macmillan |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-030-96180-0_18 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:180161 |