Adam, Alison. 1995. “A Feminist Critique of Artificial Intelligence.” European Journal of Women’s Studies 2 (3): 355–77.
Agre, Philip E. 1995. “The Soul Gained and Lost. Artificial Intelligence as a Philosophical Project.” Stanford Humanities Review 4 (2): 1–19.
Apprich, Clemens, Wendy Hui Kyong Chun, Florian Cramer, and Hito Steyerl. 2018. Pattern Discrimination. Meson Press.
Arun, Chinmayi. 2019. “AI and the Global South: Designing for Other Worlds.”
Benanav, Aaron. 2019a. “Automation and the Future of Work I.” New Left Review II (119): 5–38.
———. 2019b. “Automation and the Future of Work II.” New Left Review II (120): 117–46.
Benjamin, Ruha. 2019. Race after Technology: Abolitionist Tools for the New Jim Code. John Wiley & Sons.
Box, George E. P. 1979. “Robustness in the Strategy of Scientific Model Building.” In Robustness in Statistics, 201–236. Elsevier.
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.
Breiman, Leo. 2001. “Statistical Modeling: The Two Cultures.” Statistical Science 16 (3): 199–231.
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.
Crawford, Kate, and Trevor Paglen. 2019. Excavating AI: The Politics of Images in Machine Learning Training Sets.
Damerow, Peter, and Wolfgang Lefèvre. 1996. “Tools of Science.” In Abstraction and Representation. Essays on the Cultural Evolution of Thinking, 395–404. Dordrecht: Kluwer.
Daston, Lorraine. 2017. “The History of Science and the History of Knowledge.” KNOW: A Journal on the Formation of Knowledge 1 (1): 131–154.
———. 2018. “Calculation and the Division of Labor, 1750-1950.” Bulletin of the German Historical Institute 62 (Spring): 9–30.
Desrosières, Alain. 2002. The Politics of Large Numbers: A History of Statistical Reasoning. Harvard University Press.
Dick, Stephanie. 2015. “Of Models and Machines: Implementing Bounded Rationality.” Isis 106 (3): 623–634.
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.
Hacking, Ian. 1990. The Taming of Chance. Cambridge University Press.
Heaven, Will Douglas. 2020. “Our Weird Behavior during the Pandemic Is Messing with AI Models.” MIT Technology Review, no. May.
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.
Lipton, Zachary C. 2016. “The Mythos of Model Interpretability.” In 2016 ICML Workshop on Human Interpretability in Machine Learning, New York, NY.
Malik, Momin M. 2020. “A Hierarchy of Limitations in Machine Learning.” ArXiv Preprint ArXiv:2002.05193.
Mazzocchi, Fulvio. 2015. “Could Big Data Be the End of Theory in Science? A Few Remarks on the Epistemology of Data-Driven Science.” EMBO Reports 16 (10): 1250–1255.
McQuillan, Dan. 2018. “People’s Councils for Ethical Machine Learning.” Social Media+ Society 4 (2).
Offert, Fabian, and Peter Bell. 2020. “Perceptual Bias and Technical Meta-Images. Critical Machine Vision as a Humanities Challenge.” AI & Society.
Östling, Johan, David Larsson Heidenblad, Erling Sandmo, Anna Nilsson Hammar, and Kari Nordberg. 2018. “The History of Knowledge and the Circulation of Knowledge: An Introduction.” In Circulation of Knowledge: Explorations in the History of Knowledge, 9–33. Nordic Academic Press.
Pasquinelli, Matteo. 2017. “Arcana Mathematica Imperii: The Evolution of Western Computational Norms.” In Former West: Art and the Contemporary after 1989, 281–294.
Pasquinelli, Matteo, and Vladan Joler. 2020. “The Nooscope Manifested: Artificial Intelligence as Instrument of Knowledge Extractivism.” KIM HfG Karlsruhe and Share Lab.
Rosenblueth, Arturo, and Norbert Wiener. 1945. “The Role of Models in Science.” Philosophy of Science 12 (4): 316–321.
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.
The Radical AI Project.
Politically Mathematics Collective.
AI Now Institute.
Histories of Artificial Intelligence.
Algorithmic Justice League.

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

© 2020 | KIM HfG Karlsruhe