Graph · Publication
Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence
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03 · Background
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Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence is a 2021 book by the AI-and-power scholar Kate Crawford, published by Yale University Press in eBook on 6 April 2021 (ISBN 9780300252392) and in paperback on 16 August 2022 (ISBN 9780300264630), 336 pages with 31 black-and-white illustrations, with the hardcover edition (ISBN 9780300209570) following on 25 May 2021. It is the publication-side anchor of the extractive / material AI-critique register of the algorithmic-accountability movement — the named single book most often cited as moving the public conversation about AI away from abstract ethics frameworks and toward a power-and-political-economy analysis grounded in the minerals, water, energy, labour, and data the systems physically depend on. The book has been translated into twelve languages and has won three international prizes, including the 2022 Sally Hacker Prize from the Society for the History of Technology and the 2022 ASIS&T Best Information Science Book of the Year, alongside the 2021 CHOICE Outstanding Academic Titles recognition, and was named one of the best books on technology of 2021 by the Financial Times and one of the New Scientist year-end booklist picks. Published blurbs include Karen Hao's "It's a masterpiece, and I haven't been able to stop thinking about it" and Virginia Dignum's "Meticulously researched and superbly written", with endorsements from Ruha Benjamin, Simone Browne, Wendy Hui Kyong Chun, Peter Galison, Geoffrey Bowker, Alondra Nelson, and Lucy Suchman.
The book's central move is to recast artificial intelligence as a technology of extraction. The opening framing on Crawford's own author-site book page is that AI relies on "dehumanizing extractive practices" rather than appearing neutral or objective, and that the technology reflects "power systems benefiting few at the expense of many"; the Yale publisher copy formalises the argument as AI being a technology of extraction "from the minerals drawn from the earth to the labor pulled from low-wage information workers". The substantive evidentiary base walks chapter-by-chapter through Big Tech's exploitation of natural resources via lithium mining and of labour via Amazon warehouses and Mechanical Turk; the construction of training datasets without consent on ImageNet and the bias-producing structure of the Amazon hiring classifier; the problematic foundations of affective-computing emotion-recognition systems; surveillance technology and US military applications including Project Maven; the framing of AlphaGo as computational brute force rather than otherworldly intelligence; and a closing critique of tech-billionaire private-spaceflight fantasies. Karen Hao's 23 April 2021 MIT Technology Review feature "Stop talking about AI ethics. It's time to talk about power." — the named mainstream specialist-press review most often paired with the book in subsequent citation — traces the case-study chain from Silicon Valley to the Clayton Valley lithium-mining operations in Nevada, treats the Amazon fulfilment centres as the labour-mechanisation case, reads Samuel Morton's 19th-century skull collection as the historical pre-figuration of contemporary algorithmic classification, and carries the often-cited Crawford line that AI "is neither artificial nor intelligent — we're just looking at forms of statistical analysis at scale" inheriting the problems of its training data, with the closing call to "contend with the environmental footprint of the systems and the very real forms of labor exploitation".
The book is grounded in Crawford's named professional trajectory across academic, industry-research, and art-research registers. Crawford holds a PhD from the University of Sydney, is Senior Principal Researcher at Microsoft Research New York in the Social Media Collective, Research Professor at the University of Southern California, and was the inaugural Visiting Chair of AI and Justice at the École Normale Supérieure in Paris (2019); she is the named co-founder and former director of research of the AI Now Institute at NYU and a former visiting professor at the MIT Center for Civic Media, and a co-founder of FATE (Fairness, Accountability, Transparency and Ethics in AI). The book is the third in a sequence of Crawford-led works opening AI's material substrate to public visibility: it sits downstream of the named long-running art-research collaborations Anatomy of an AI System with Vladan Joler (the 2018 Amazon-Echo supply-chain map subsequently acquired by MoMA and held in the permanent collections of the V&A, the Ars Electronica Center, and the Design Museum London) and Training Humans with Trevor Paglen (2019), and upstream of the named Calculating Empires: A Genealogy of Technology and Power since 1500 exhibition with Vladan Joler that won the Silver Lion at the 2025 Venice Architecture Biennale. The book's research-side continuation is the Knowing Machines Project, the Sloan-Foundation-funded transatlantic research project Crawford directs — "a research project tracing the histories, practices, and politics of how machine learning systems are trained to interpret the world", whose ongoing outputs include the Calculating Empires exhibition, Models all the Way Down visual investigation, Synthetic Media collection, Bird in hand collection, Knowing Legal Machines collection, the Generative AI Legal Explainer, the 9 ways to see a Dataset essays, A Critical Field Guide for Working with Machine Learning Datasets, and the Critical Dataset Studies reading list — the named institutional vehicle through which the book's dataset-and-classification argument is being carried forward into a continuing research programme.
Within the corpus, Atlas of AI sits as the extractive / material / planetary-costs entry of the algorithmic-accountability foundational-artefact register, joining the corpus's other publication-side anchors — Weapons of Math Destruction (2016), the cross-domain public-policy popular-book anchor; Algorithms of Oppression (2018), the Black-feminist search-engine-bias anchor; Automating Inequality (2018), the US welfare and social-services algorithmic-harm anchor; Design Justice (2020), the participatory-design framework-text monograph; Unmasking AI (2023), the memoir-and-manifesto book of the Algorithmic Justice League; and the peer-reviewed-paper anchors Gender Shades (2018), Stochastic Parrots (2021), and the TESCREAL Bundle essay — as the publication-side artefacts on which the make-AI-good movement's grassroots organising routinely rests. The book is distinct from those companions in two specific respects. First, where the Eubanks, Noble, and O'Neil trio names a specific class of algorithmic harm in a specific US-domestic institutional setting (welfare administration, search-engine bias, cross-domain risk-scoring), Atlas of AI shifts the camera one level out to the physical substrate the systems sit on — the lithium mines, the warehouse-labour discipline, the dataset-construction supply chain, the surveillance-state procurement layer — supplying the framing on which the corpus's data-centre-organising publication arc (the MediaJustice Southern-regional report) and the climate-and-Big-Tech publication arc (the Kairos Fellowship Google's Eco-Failures report on emissions accounting) subsequently rest. Second, it is the named book that connects the algorithmic-accountability canon to a continuing art-and-research practice operating at museum scale — the Anatomy of an AI System and Calculating Empires exhibitions and the Knowing Machines Project research outputs together comprise the practice-side translation parallel to the Our Data Bodies participatory-research continuation Eubanks built on the Automating Inequality side, the ORCAA services-consulting continuation O'Neil established on the Weapons of Math Destruction side, and the Center for Critical Internet Inquiry (C2i2) academic-research continuation Noble established on the Algorithms of Oppression side — but operating at a different register (museum and field-research rather than non-profit or consulting).
04 · Sources
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6 sources listed from the pinned corpus. Links are shown only when the source URL is a valid HTTP(S) address.
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en.wikipedia.org
Checked 2026-05-19Wikipedia entry on Atlas of AI — independent secondary source for the May 2021 Yale University Press hardcover (ISBN 9780300209570, 336 pages), the named central thesis that AI is a technology of extraction from minerals, labour, data, and the environment, the named chapter-by-chapter structure (Big Tech extraction of natural resources and labour via Amazon warehouses and Mechanical Turk; dataset building without consent on ImageNet and the Amazon hiring classifier; affective-computing emotion-recognition systems; surveillance and Project Maven; AlphaGo as computational brute force; the closing critique of tech-billionaire private-spaceflight fantasies), the named field-site case studies (Thacker Pass lithium mine in Nevada's Clayton Valley, Amazon warehouses, ImageNet, Cambridge Analytica, Project Maven, Palantir), the named CHOICE Outstanding Academic Titles 2021 recognition, the named Financial Times and New Scientist year-end booklist inclusions, and the named reviewers Karen Hao (MIT Technology Review), Sue Halpern (New York Review of Books), Michael Spezio (Science), Virginia Dignum (Nature), and Anais Resseguier (AI and Ethics)
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en.wikipedia.org
Checked 2026-05-19Wikipedia entry on Kate Crawford — primary secondary source for Crawford's named professional trajectory: PhD from the University of Sydney, Senior Principal Researcher at Microsoft Research New York (Social Media Collective), co-founder and former director of research at the AI Now Institute at NYU, former visiting professor at the MIT Center for Civic Media, former associate professor at the Journalism and Media Research Centre at UNSW; the named art-project collaborations *Anatomy of an AI System* with Vladan Joler (2018, Beazley Design of the Year 2019), *Training Humans* with Trevor Paglen (2019), and *Calculating Empires: A Genealogy of Technology and Power since 1500* with Vladan Joler (Silver Lion at Venice Architecture Biennale 2025); her named inaugural AI and Justice visiting chair at École Normale Supérieure in Paris (2019); and her named prior book *Adult Themes — Rewriting the Rules of Adulthood* (2006) and the named Manning Clark National Cultural Award (2006) and Max Crawford Medal for outstanding scholarship (2008)
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yalebooks.yale.edu
Checked 2026-05-19Yale University Press official book page for Atlas of AI — primary source for the eBook 6 April 2021 and paperback 16 August 2022 release dates, the paperback ISBN 9780300264630 and eBook ISBN 9780300252392, the named 336-page length with 31 black-and-white illustrations, the named publisher framing of AI as a technology of extraction "from the minerals drawn from the earth to the labor pulled from low-wage information workers", the named *Wall Street Journal* "Five Best Books to Read to Get Smart about AI" inclusion, the named endorsements from Karen Hao ("It's a masterpiece, and I haven't been able to stop thinking about it") and Virginia Dignum ("Meticulously researched and superbly written"), and the named 2022 Sally Hacker Prize from the Society for the History of Technology and the named 2022 ASIS&T Best Information Science Book of the Year recognitions alongside the 2021 CHOICE Outstanding Academic Titles inclusion
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katecrawford.net
Checked 2026-05-19Kate Crawford's own author-site book page for Atlas of AI — primary source for Crawford's own scope-statement that AI relies on "dehumanizing extractive practices" rather than appearing neutral or objective and that the technology reflects power systems benefiting few at the expense of many, the named *Financial Times* best-book-of-2021 inclusion, the named twelve-language translation count, the named statement that the book has won three international prizes, and the named blurb endorsers Ruha Benjamin, Simone Browne, Wendy Hui Kyong Chun, Peter Galison, Geoffrey Bowker, Alondra Nelson, and Lucy Suchman; together with the named running affiliations recorded on the site (Research Professor at the University of Southern California; Senior Principal Researcher at Microsoft Research New York; Inaugural Visiting Chair of AI and Justice at École Normale Supérieure, Paris; Director of the Knowing Machines Project; co-founder of FATE — Fairness, Accountability, Transparency and Ethics in AI; co-founder of the AI Now Institute at NYU)
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technologyreview.com
Checked 2026-05-19Karen Hao's 23 April 2021 MIT Technology Review feature "Stop talking about AI ethics. It's time to talk about power." — mainstream specialist-press review corroborating the book's named paradigm-shift framing from abstract ethics conversations toward power-and-accountability discussions centred on extraction, the named case-study chain running from Silicon Valley to the Clayton Valley lithium-mining operations in Nevada, the named treatment of Amazon fulfilment centres as the labour-mechanisation case, the named treatment of Samuel Morton's 19th-century skull collection as the historical pre-figuration of modern classification systems, and the named "Anatomy of an AI System" supply-chain mapping of the Amazon Echo as the visual-essay precursor the book formalises into a single-volume argument; the same Hao review carries the often-cited Crawford framing that AI "is neither artificial nor intelligent — we're just looking at forms of statistical analysis at scale" inheriting the problems of their training data, and the closing call to "contend with the environmental footprint of the systems and the very real forms of labor exploitation"
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knowingmachines.org
Checked 2026-05-19Knowing Machines Project site — primary source for the named transatlantic research-project continuation Crawford directs (Sloan-Foundation-funded; described as "a research project tracing the histories, practices, and politics of how machine learning systems are trained to interpret the world"), and for the named ongoing research outputs (*Calculating Empires* exhibition; *Models all the Way Down* visual investigation; *Synthetic Media* collection; *Understanding the Work of Dataset Creators* interviews; *Bird in hand* collection; *Generative AI Legal Explainer*; *Knowing Legal Machines* collection; *9 ways to see a Dataset* essays; *A Critical Field Guide for Working with Machine Learning Datasets*; *Critical Dataset Studies* reading list); included as the corpus-relevant practice-side continuation of Atlas of AI's dataset-and-classification argument, parallel to the role Our Data Bodies plays for Eubanks's *Automating Inequality* and the role the Center for Critical Internet Inquiry plays for Noble's *Algorithms of Oppression*
Source: entities/publications/pub-atlas-of-ai.md in movement-graph at pin 3cc1a36.