Atlas of AI book cover

Atlas of AI by Kate Crawford Summary

Atlas of AI
Kate Crawford
3.95 (2570 Reviews)
AI
Politics
Technology
Обзор
Ключевые Выводы
Автор
Часто Задаваемые Вопросы

Overview of Atlas of AI

Kate Crawford's "Atlas of AI" exposes the hidden planetary costs of artificial intelligence. Called "a masterpiece" by MIT Technology Review editors, this Wall Street Journal top-five AI book reveals how our digital future fuels inequality and environmental devastation. What price are we really paying for AI?

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Ключевые выводы

1

The Hidden Material Reality Behind AI's Digital Facade

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When you picture artificial intelligence, you likely imagine sleek robots or voice assistants responding to your commands. But beneath this glossy veneer lies a far more complex reality. AI isn't simply code floating in the digital ether-it's a massive industrial system built on extraction, exploitation, and classification that shapes our world in profound ways. The truth is that AI is neither artificial nor intelligent. It's deeply material, requiring vast amounts of natural resources and human labor to function. From lithium mines in Nevada to rare earth processing facilities in Inner Mongolia, AI's physical foundation spans the globe. Despite the ethereal "cloud" metaphors, AI infrastructure is profoundly material and environmentally damaging. A single natural language processing model can produce carbon emissions equivalent to five cars' lifetime output, while data centers already match aviation's carbon footprint. What makes this reality so insidious is how deliberately it's hidden from view. Tech companies project an image of sustainability while concealing enormous energy consumption. They claim carbon neutrality through offset credits while simultaneously licensing AI technology to fossil fuel companies. The scale and complexity of this material infrastructure is obscured by intellectual property laws and technical complexity-creating a modern "megamachine" that, like the Manhattan Project, operates through secrecy and coordination.

2

The Invisible Workforce Behind "Automated" Systems

3

The Extractive Logic of Data Collection

4

The Politics of Classification and Categorization

5

The Myth of Reading Emotions from Faces

6

The Military Origins of AI and Its Surveillance Legacy

7

Challenging AI's Power Structures and Enchanted Determinism

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