Reflection AI: feeding the machine - the hidden labour behind AI tools and ethical implications for higher education
Mark Graham,Oğuz Alyanak,Jonas CL Valente
TLDR
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.
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.
