What if the cause of Americans’ collective cognitive decline is, simply, each other?

Cientistas políticos e antropólogos que estudam a evolução do fenômeno desde 2018 afirmaram ao GLOBO que a maior privação de liberdade pode afetar o papel de Bolsonaro como cabo eleitoral e fragmentar...

Governor-elect Abigail Spanberger says the University of Virginia should wait to pick a new president.

Archiving Machines advances our understanding of memory, information, and data by charting the struggle between the computing technologies that archive data ...

Meta projected 10% of its 2024 revenue would come from ads for scams and banned goods, and it internally estimates that its platforms show users 15 billion scam ads a day, company documents show.

Moradores, indígenas e entidades pedem ao MPF para barrar o licenciamento.

This article interrogates the widespread narrative of Artificial Intelligence (AI) as autonomous, intelligent, and self-sufficient, and instead centers on the largely invisible human labor that sustains these systems. Drawing on the frameworks of heteromation and human infrastructure, we analyze how AI systems are deeply reliant on distributed networks of ghost workers, crowdworkers, and microtaskers, often working in precarious conditions, to perform essential and low-paid tasks such as content moderation, data annotation, and fact-checking. Far from being fully automated, these systems operate as sociotechnical assemblages where algorithmic processes are scaffolded by fragmented, hidden, and undervalued human work. This article explores how platforms like Amazon Mechanical Turk and Appen organize and obscure this labor through algorithmic management and cultural erasure, creating an illusion of machinic intelligence while extracting value from unpaid or underpaid workers. By examining examples ranging from self-driving car training to misinformation moderation, we argue that understanding AI requires acknowledging the human infrastructures that animate it. This perspective challenges dominant techno-deterministic ideologies and reframes ethical debates around AI to focus on labor, visibility, and exploitation. Ultimately, this article calls for critical attention to the political economy of AI and insists that any ethical framework for AI must begin with the recognition and fair treatment of the human labor that makes it function.

Olivia Guest & Iris van Rooij urge teachers and scholars to reject tools that commodify learning, deskill students, and promote illiteracy.

Apply for Digital Technology for Democracy Postdoctoral Research Fellow job with University of Virginia in Charlottesville, Virginia, United States of America. Research at University of Virginia