Reflection AI: feeding the machine - the hidden labour behind AI tools and ethical implications for higher education

Journal article

Abstract:: As university instructors integrate AI tools, such as large language models (LLMs) into their pedagogy, they must grapple with the ethical and practical implications ofthese technologies. This reflection examines the overlooked labour of Cloudworkers and data workers whose contributions make AI systems functional. Drawing on insights obtained from Fairwork’s Cloudwork and AI research, 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 practises through education, policy, and institutional intervention. By centring the experiences of cloudworkers and data enrichment employees, the article urges various stakeholders to foster a more ethical approach to AI in higher education.

Files:: Alyanak_et_al_2025_Feeding_the_machine.pdf

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Language:: English
Keywords:: artificial intelligence

working conditions

fairwork

higher education

AI ethics
Pubs id:: 2242468
Local pid:: pubs:2242468
Deposit date:: 2025-07-11
ARK identifier:: ark:/29072/ora_c2a84890b3294e59ab353e22d78f0e82

Copyright holder:: Graham et al.
Rights statement:: © 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) and the copyright owner(s) 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.

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