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FEEDING THE MACHINE by James Muldoon

FEEDING THE MACHINE

The Hidden Human Labor Powering A.I.

by James Muldoon & Mark Graham & Callum Cant

Pub Date: Aug. 6th, 2024
ISBN: 9781639734962
Publisher: Bloomsbury

A look beyond the hype surrounding AI.

As researchers at the Oxford Internet Institute, Muldoon, Graham, and Cant have conducted a series of field studies concerning AI’s tangible inputs and impacts, from human labor to undersea cables to the energy needed for data storage and processing. This synthesis of their studies frames AI as an “extraction machine” that exacerbates rather than corrects centuries of global inequities and patterns of oppression. In each chapter, the authors examine a different, problematic node in the supply chain for AI’s large language models, centering individuals such as data annotators and fulfillment workers to illustrate the intentional opacity and profit-driven domination of a small group of tech companies that are quickly consolidating power in the age of AI. “The technology capitalism develops isn’t neutral,” the authors write. Rather, “it is built in the image of the system that birthed it.” While the authors are well aware of potential harmful long-term implications in AI’s development, use, and manipulation, their mission is not to incite hand wringing over apocalyptic hypotheticals. Rather than wallowing in such fatalism, they focus on how even the present reality of AI erects and strengthens barriers to justice, equality, and creativity, and they set forth recommendations for stepping off the current course. The authors’ own sensitivities and proclivities are evident, including hyperexcitement about the ability of labor unions to lead such a corrective, and many of the alarms they sound are not particular to AI, leading some sections to wander and lose urgency. Still, their look beneath the hood of some of technology’s most heralded advances brings to public awareness critical issues regarding AI, its colonial roots, and its exploitative tendencies that society would do well to discuss and debate sooner rather than later.

A sobering and timely—if sometimes distracted—study of AI.