Graph · Publication
Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
01 · In focus
One publication, in the field.
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publication
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03 · Background
From the source record.
Body prose as it appears in movement-graph’s published markdown for this entity. Links to other corpus entities resolve to their graph page; links to deeper repo paths are kept as text so the page does not invent a route.
Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor is a 2018 book by the political scientist and data-justice scholar Virginia Eubanks, published by St. Martin's Press on 23 January 2018 (hardcover ISBN 9781250074317, 272 pages) and subsequently reissued in paperback by Picador. It is the publication-side anchor of the welfare-and-social-services register of the algorithmic-accountability movement — the named single book most often cited as bringing the harms of algorithmic public-services systems (welfare-eligibility automation, homelessness-services allocation, child-welfare predictive-risk modelling) into general public and policy circulation, and the named US-side companion to the corpus's French-language welfare-algorithm publication anchor of the La Quadrature du Net CAF investigation. The book was named winner of the 2019 Lillian Smith Book Award, the 2018 McGannon Center Book Prize, and shortlisted for the 2018 Goddard Riverside Stephan Russo Book Prize for Social Justice, and was endorsed in published blurbs by Naomi Klein ("This book is downright scary"), Alondra Nelson ("powerful, sobering, and humane book"), and Dorothy Roberts ("must-read for everyone concerned about the modern tools of inequality"), with the New York Times Book Review calling it "Riveting… technology is no substitute for justice".
The book's central move is to name and develop a class of algorithmic public-services system Eubanks calls the digital poorhouse — the working argument, as Wikipedia summarises it, that contemporary digital welfare-administration tools draw a continuous lineage from the 19th-century physical poorhouse to the 21st-century algorithmic systems that "control and contain poor people using technology". The named substantive evidentiary base is three case studies: the Indiana welfare-eligibility automation contracted out under Governor Mitch Daniels, which produced a 54% increase in benefit denials between 2006 and 2008; the Los Angeles coordinated-entry system allocating homeless-services resources across the county; and the Allegheny Family Screening Tool, the predictive-risk model used by Allegheny County (Pittsburgh) in child-welfare investigations. The opening framing on Eubanks's own author-site book page is that "automated systems control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud", and that the book's domain scope is "data mining, policy algorithms, and predictive risk models on poor and working-class people in America" — the named scope-statement on which subsequent grassroots organising on algorithmic welfare-administration in the United States routinely rests. The Atlantic's 15 February 2018 feature on the book by Tanvi Misra and the NPR All Tech Considered piece of 19 February 2018 are the named mainstream-press features that carried the book's argument into general circulation, both treating the Allegheny Family Screening Tool as the book's most-developed case study and the digital poorhouse framing as its most-propagated single formulation.
The book is grounded in Eubanks's named professional trajectory across the academic-and-community boundary. Eubanks earned her PhD in Science and Technology Studies from Rensselaer Polytechnic Institute in 2004 with the dissertation "Popular technology: Citizenship and inequality in the information economy", and is now Associate Professor in the Department of Political Science at the University at Albany, SUNY. The book was written during her 2016-17 New America Fellowship, the named research-residency window in which the three case studies were assembled. Her prior book Digital Dead End: Fighting for Social Justice in the Information Age (MIT Press, 2011) established the popular-technology and community-research register the later book formalises into a single-volume case-study sequence, and she has subsequently co-edited Ain't Gonna Let Nobody Turn Me Around: Forty Years of Movement Building with Barbara Smith and Alethia Jones. Across the same span she has been a named co-founder of Our Data Bodies (ODB), the participatory-research collective whose 2018 Reclaiming our data report Eubanks co-authored with Mariella Saba, Tamika Lewis, Seeta Peña Gangadharan, and Tawana Petty — the named organisational continuation of the community-research method the book argues for in its final dismantling chapter, working across Charlotte, Detroit, and Los Angeles as the practice-side translation of the book's argument into community-led data-justice organising. Eubanks's named appearance in Shalini Kantayya's 2020 documentary Coded Bias — alongside Cathy O'Neil, Safiya Noble, and Joy Buolamwini — is the named single mainstream-media event most often paired with the book in subsequent citation as the multi-author register of the early-2020s algorithmic-accountability public conversation.
Within the corpus, Automating Inequality sits as the welfare-and-public-services 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; 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) and Stochastic Parrots (2021) — 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, it is the named book of the trio of early-2018 popular-press algorithmic-accountability texts — Algorithms of Oppression (February 2018), Automating Inequality (January 2018), and the post-publication wave of attention to Weapons of Math Destruction (originally 2016, in second printing) — that names the welfare-administration and child-welfare layers of the US administrative state as the substantive sites where algorithmic harm is concretely produced, where the companion books address search engines and cross-domain models more generally. Second, it is the named US-side popular-press anchor of a corpus pair with the French-language LQDN CAF report of November 2023 — both works treat algorithmic risk-scoring of welfare beneficiaries as the substantive site of algorithmic harm under contemporary welfare-state administration, with the book's digital poorhouse framing and the LQDN report's algorithme de la honte / algorithme de notation framing as the named US and French civil-society short-forms for the same phenomenon. The book's downstream organisational continuation through Our Data Bodies and the participatory data-justice strand running through Tawana Petty and the Detroit Community Technology Project makes it the corpus's clearest single example of a book whose argument has been carried by its co-author into a continuing community-research practice — the practice-side translation parallel to 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.
04 · Sources
Where this came from.
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 Automating Inequality — independent secondary source for the 2018 St. Martin's Press publication, the ISBN 9781250074317, the book's three named case studies (the Indiana welfare-eligibility automation under Governor Mitch Daniels that produced a 54% increase in benefit denials between 2006 and 2008; the Los Angeles coordinated-entry system allocating homeless-services resources; the Allegheny Family Screening Tool predictive-risk model used in child-welfare investigations in Pittsburgh / Allegheny County, Pennsylvania), the named central concept the "digital poorhouse" the book introduces to connect 19th-century physical poorhouses with 21st-century algorithmic welfare-control systems, the Financial Times' named comparison of the book with Algorithms of Oppression as the paired works opening algorithmic-accountability to a non-technical readership, and the named 2018 Goddard Riverside Stephan Russo Book Prize for Social Justice shortlisting
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en.wikipedia.org
Checked 2026-05-19Wikipedia entry on Virginia Eubanks — primary secondary source for Eubanks' position as Associate Professor in the Department of Political Science at the University at Albany, SUNY, her 2004 PhD in Science and Technology Studies from Rensselaer Polytechnic Institute with the dissertation "Popular technology: Citizenship and inequality in the information economy", her 2016-17 New America Fellowship under which the book was written, her named co-founding role with Our Data Bodies, her prior book *Digital Dead End: Fighting for Social Justice in the Information Age* (MIT Press, 2011), her named co-edited volume *Ain't Gonna Let Nobody Turn Me Around: Forty Years of Movement Building* with Barbara Smith and Alethia Jones, her named recognitions (2019 Lillian Smith Book Award; 2018 McGannon Center Book Prize; 2018 Goddard Riverside Stephan Russo Book Prize for Social Justice shortlist), her appearance in the 2020 documentary *Coded Bias* directed by Shalini Kantayya, and her named founding role in the Popular Technology Workshops and Our Knowledge, Our Power (OKOP, 2005) community-research collectives
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virginia-eubanks.com
Checked 2026-05-19Virginia Eubanks' own author-site book page for Automating Inequality — primary source for the named programmatic framing that "automated systems control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud" and for the named domain scope "data mining, policy algorithms, and predictive risk models on poor and working-class people in America", the recorded named endorsements from Naomi Klein ("This book is downright scary"), the *New York Times Book Review* ("Riveting… technology is no substitute for justice"), Alondra Nelson ("powerful, sobering, and humane book"), and Dorothy Roberts ("must-read for everyone concerned about the modern tools of inequality"), and the named cited individual cases the book opens with (a woman in Indiana whose benefits were terminated while she was dying; a Pennsylvania family living in fear of losing their daughter due to fitting a statistical profile)
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npr.org
Checked 2026-05-19NPR All Tech Considered (19 February 2018) feature "Automating Inequality: Algorithms In Public Services Often Fail The Most Vulnerable" — mainstream-news source on publication corroborating the book's named central argument that algorithmic public-services systems disproportionately fail the most vulnerable, the named "digital poorhouse" framing carried forward as the book's most-propagated single formulation, and the named release window placing the book at the head of the spring 2018 algorithmic-accountability publication wave alongside the second-printing reception of *Weapons of Math Destruction* and the February 2018 release of *Algorithms of Oppression*
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theatlantic.com
Checked 2026-05-19The Atlantic (15 February 2018) feature by Tanvi Misra "When Welfare Decisions are Left to Algorithms" — mainstream-news source corroborating the book's named substantive argument that delegating welfare-eligibility, homelessness-services, and child-welfare-investigation decisions to algorithmic systems entrenches and amplifies the historical mistreatment of poor and working-class Americans, the named treatment of the Allegheny Family Screening Tool as the book's most-developed case study, and the named comparison framing the book alongside Cathy O'Neil's and Safiya Noble's contemporaneous books as the trio of early-2018 popular-press algorithmic-accountability texts
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odbproject.org
Checked 2026-05-19Our Data Bodies (ODB) project working-output page (the Detroit Project Green Light report) — corpus-internal cross-citation supporting Eubanks' named co-founding membership of Our Data Bodies, the participatory-research collective whose 2018 *Reclaiming our data* report Eubanks co-authored with Mariella Saba, Tamika Lewis, Seeta Peña Gangadharan, and [Tawana Petty](../voices/voice-tawana-petty.md), and which is the named organisational continuation of the community-research method the book argues for in its final-chapter dismantling section; ODB's working programme across Charlotte, Detroit, and Los Angeles is the named example most often paired with the book in subsequent citation as the practice-side translation of the book's argument into community-led data-justice organising
Source: entities/publications/pub-automating-inequality.md in movement-graph at pin 3cc1a36.