ORIGINAL RESEARCH article
Front. Commun.
Sec. Media, Creative, and Cultural Industries
Volume 10 - 2025 | doi: 10.3389/fcomm.2025.1614817
This article is part of the Research TopicTeaching and Assessing with AI: Teaching Ideas, Research, and ReflectionsView all 12 articles
Feeding the Machine: The Hidden Labour Behind AI Tools and Ethical Implications for Higher Education
Provisionally accepted
- 1University of Oxford, Oxford, United Kingdom
- 2Oxford Internet Institute, Social Sciences Division, University of Oxford, Oxford, England, United Kingdom
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As university instructors integrate AI tools, such as large language models (LLMs) into their pedagogy, they must grapple with the ethical and practical implications of these technologies. This reflection examines the overlooked labour of Cloudworkers and data workers whose contributions make AI systems functional. It argues for the adoption of the Fairwork scoring system, as a methodology, as well as a heuristic, to guide ethical engagement with AI and urges higher education instructors and students to advocate for improved working conditions in AI supply chains. Additionally, it explores the multifaceted impacts of AI technologies on global labour markets, highlighting pathways to more equitable practices through education, policy, and institutional intervention.
Keywords: artificial intelligence, Working conditions, Fairwork, Higher ed, AI ethics
Received: 02 May 2025; Accepted: 25 Jun 2025.
Copyright: © 2025 Graham, Alyanak and Valente. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Oğuz Alyanak, University of Oxford, Oxford, United Kingdom
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