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Trevor Paglen’s New Book Says AI Is Rewriting What Images Do

Artist Trevor Paglen has published a new book, *How to See Like a Machine: Images After AI*, which argues that generative AI and computer vision are fundamentally changing how images function in culture. Drawing on his decade-long practice, Paglen contends that images are no longer merely representations for human interpretation but have become operational tools—'activations' that trigger automated responses and shape reality. He cites examples such as surveillance cameras at grocery stores, the Samsara navigation system in trucks, and the ImageNet database to illustrate how machine vision systems normalize surveillance in service of capital, a phenomenon he terms 'machine realism.'

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Artist Trevor Paglen and AI researcher Kate Crawford have launched ImageNetRoulette, a viral digital art project that uses artificial intelligence to label user-uploaded photos. The project, which is part of their "Training Humans" exhibition at Fondazione Prada, gained massive social media traction by generating often offensive or bizarre classifications for users. By exposing the problematic labels—ranging from "mediatrix" to racial slurs and criminal accusations—the creators aim to reveal the deep-seated systemic biases embedded in the ImageNet database, one of the world's most influential AI training sets.