Bates, J. orcid.org/0000-0001-7266-8470, Gerakopoulou, E. and Checco, A. (2023) Addressing labour exploitation in the data science pipeline: views of precarious US-based crowdworkers on adversarial and co-operative interventions. Journal of Information, Communication and Ethics in Society, 21 (3). ISSN 1477-996X
Abstract
Purpose
Underlying much recent development in data science and artificial intelligence (AI) is a dependence on the labour of precarious crowdworkers via platforms such as Amazon Mechanical Turk. These platforms have been widely critiqued for their exploitative labour relations, and over recent years, there have been various efforts by academic researchers to develop interventions aimed at improving labour conditions. The aim of this paper is to explore US-based crowdworkers’ views on two proposed interventions: a browser plugin that detects automated quality control “Gold Question” (GQ) checks and a proposal for a crowdworker co-operative.
Design/methodology/approach
The authors interviewed 20 US-based crowdworkers and undertook a thematic analysis of collected data.
Findings
The findings indicate that US-based crowdworkers tend to have negative and mixed feelings about the GQ detector, but were more enthusiastic about the crowdworker co-operative.
Originality/value
Drawing on theories of precarious labour, this study suggests an explanation for the findings based on US-based workers’ objective and subjective experiences of precarity. The authors argue that for US-based crowdworkers “constructive” interventions such as a crowdworker co-operative have more potential to improve labour conditions.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023, Emerald Publishing Limited. This is an author-produced version of a paper subsequently published in Journal of Information, Communication and Ethics in Society. This version is distributed under the terms of the Creative Commons Attribution-NonCommercial Licence (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You may not use the material for commercial purposes. |
Keywords: | Crowdwork; Labour ethics; Precarity; Data; Artificial intelligence |
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: | 05 May 2023 08:57 |
Last Modified: | 03 Oct 2024 15:00 |
Status: | Published |
Publisher: | Emerald |
Refereed: | Yes |
Identification Number: | 10.1108/JICES-08-2022-0069 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:198670 |
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