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Boyd, Danah, and Kate Crawford. 2012. “Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon.” Information, Communication & Society 15 (5): 662–679.
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Burke, Peter. 2013. Social History of Knowledge: From Gutenberg to Diderot. John Wiley & Sons.
Cardon, Dominique, Jean-Philippe Cointet, and Antoine Mazières. 2018. “Neurons Spike Back. The Invention of Inductive Machines and the Artificial Intelligence Controversy.” Translated by Elizabeth Libbrecht. Réseaux 211 (5): 173–220.
Castelle, Michael. 2018. “Deep Learning as an Epistemic Ensemble.” 2018. https://castelle.org/pages/deep-learning-as-an-epistemic-ensemble.html.
Crawford, Kate, and Trevor Paglen. 2019. Excavating AI: The Politics of Images in Machine Learning Training Sets. https://www.excavating.ai/.
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Desrosières, Alain. 2002. The Politics of Large Numbers: A History of Statistical Reasoning. Harvard University Press.
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Edwards, Paul N. 2010. A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming. MIT Press.
Eubanks, Virginia. 2018. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York, NY: St. Martin’s Press.
Galison, Peter. 1997. Image and Logic: A Material Culture of Microphysics. The University of Chicago Press.
Gray, Mary L., and Siddharth Suri. 2019. Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Eamon Dolan Books.
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Heaven, Will Douglas. 2020. “Our Weird Behavior during the Pandemic Is Messing with AI Models.” MIT Technology Review, no. May. https://www.technologyreview.com/2020/05/11/1001563/covid-pandemic-broken-ai-machine-learning-amazon-retail-fraud-humans-in-the-loop/.
Jones, Matthew L. 2018. “How We Became Instrumentalists (Again): Data Positivism since World War II.” Historical Studies in the Natural Sciences 48 (5): 673–684.
Kurenkov, Andrey. 2015. “A ‘Brief’ History of Neural Nets and Deep Learning.” 2015. http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning/.
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Offert, Fabian, and Peter Bell. 2020. “Perceptual Bias and Technical Meta-Images. Critical Machine Vision as a Humanities Challenge.” AI & Society.
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Pasquinelli, Matteo, and Vladan Joler. 2020. “The Nooscope Manifested: Artificial Intelligence as Instrument of Knowledge Extractivism.” KIM HfG Karlsruhe and Share Lab. https://nooscope.ai.
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Sarasin, Philipp. 2011. “Was Ist Wissensgeschichte?” Internationales Archiv Für Sozialgeschichte Der Deutschen Literatur 36 (1): 159–172.
Schuppli, Susan. 2014. “Deadly Algorithms: Can Legal Codes Hold Software Accountable for Code That Kills?” Radical Philosophy, no. 187: 2–8.
Sculley, David, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-Francois Crespo, and Dan Dennison. 2015. “Hidden Technical Debt in Machine Learning Systems.” In Advances in Neural Information Processing Systems.


Logic magazine. https://logicmag.io
The Radical AI Project. http://radicalaiproject.org
Politically Mathematics Collective. https://www.politicallymath.in
AI Now Institute. https://ainowinstitute.org
Histories of Artificial Intelligence. https://www.hps.cam.ac.uk/about/research-projects/histories-of-ai
Algorithmic Justice League. https://ajlunited.org


Please note: the All Models bibliography is preliminary and subject to change.
You can also access the underlying public Zotero library

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