research-article

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"Guilds" as Worker Empowerment and Control in a Chinese Data Work Platform

Authors:

Milagros MiceliAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 8, Issue CSCW2

Article No.: 365, Pages 1 - 27

https://doi.org/10.1145/3686904

Published: 08 November 2024 Publication History

Abstract

Data work plays a fundamental role in the development of algorithmic systems and the AI industry. It is often performed in business process outsourcing (BPO) companies and crowdsourcing platforms, involving a global and distributed workforce as well as networks of collaborative actors. Previous work on community building among data workers centers organization and mutual support or focuses on the structuring and instrumentalization of crowdworker groups for complicated projects. We add to these lines of research by focusing on a specific form of community building encouraged and facilitated by platforms in China: guilds. Based on ethnographic work on a Chinese crowdsourcing platform and 14 semi-structured interviews with data workers, our findings show that guilds are a form of both worker empowerment and control. With this work, we add a nuanced empirical case to the interconnection of BPOs, online communities and crowdsourcing platforms in the current data production sector in China, thus expanding previous investigations on global perspectives of data production. We discuss guilds in relation to individual workers and highlight their effects on data work, including efficient coordination, enhanced standardization, and flattened power structure.

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Cited By

Sun YChen JYao BLiu JWang DMa XLu YXu YHe L(2024)Exploring Parent's Needs for Children-Centered AI to Support Preschoolers' Interactive Storytelling and Reading ActivitiesProceedings of the ACM on Human-Computer Interaction10.1145/36870358:CSCW2(1-25)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3687035
Prpa MTroiano GYao BLi TWang DGu HFarzan RLópez CCardoso Llach DQuercia DMustafa MNiu SWong-Villacrés M(2024)Challenges and Opportunities of LLM-Based Synthetic Personae and Data in HCICompanion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing10.1145/3678884.3681826(716-719)Online publication date: 11-Nov-2024
https://dl.acm.org/doi/10.1145/3678884.3681826
Yang JLi PIslam MRen S(2024)Online Allocation with Replenishable Budgets: Worst Case and BeyondACM SIGMETRICS Performance Evaluation Review10.1145/3673660.365507352:1(57-58)Online publication date: 13-Jun-2024
https://dl.acm.org/doi/10.1145/3673660.3655073
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Index Terms

"Guilds" as Worker Empowerment and Control in a Chinese Data Work Platform
1. Human-centered computing
  1. Collaborative and social computing
    1. Empirical studies in collaborative and social computing

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 8, Issue CSCW2

CSCW

November 2024

5177 pages

EISSN:2573-0142

DOI:10.1145/3703902

Editor:
Jeff Nichols
Apple Inc., United States

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Copyright © 2024 Owner/Author.

This work is licensed under a Creative Commons Attribution-NonCommercial International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 08 November 2024

Published in PACMHCI Volume 8, Issue CSCW2

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Cited By

Sun YChen JYao BLiu JWang DMa XLu YXu YHe L(2024)Exploring Parent's Needs for Children-Centered AI to Support Preschoolers' Interactive Storytelling and Reading ActivitiesProceedings of the ACM on Human-Computer Interaction10.1145/36870358:CSCW2(1-25)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3687035
Prpa MTroiano GYao BLi TWang DGu HFarzan RLópez CCardoso Llach DQuercia DMustafa MNiu SWong-Villacrés M(2024)Challenges and Opportunities of LLM-Based Synthetic Personae and Data in HCICompanion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing10.1145/3678884.3681826(716-719)Online publication date: 11-Nov-2024
https://dl.acm.org/doi/10.1145/3678884.3681826
Yang JLi PIslam MRen S(2024)Online Allocation with Replenishable Budgets: Worst Case and BeyondACM SIGMETRICS Performance Evaluation Review10.1145/3673660.365507352:1(57-58)Online publication date: 13-Jun-2024
https://dl.acm.org/doi/10.1145/3673660.3655073
Vu MWang HChen JLi ZZhao SXing ZChen C(2024)GPTVoiceTasker: Advancing Multi-step Mobile Task Efficiency Through Dynamic Interface Exploration and LearningProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676356(1-17)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676356
Yang JLi PIslam MRen SGaretto MMarin ACiucu FFanti GRighter R(2024)Online Allocation with Replenishable Budgets: Worst Case and BeyondAbstracts of the 2024 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems10.1145/3652963.3655073(57-58)Online publication date: 10-Jun-2024
https://dl.acm.org/doi/10.1145/3652963.3655073

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