“Disruption: A Manifesto,” Logic Magazine, no. 1 (March 2017) →.
Politically Mathematics collective, “Politically Mathematics Manifesto,” 2019 →.
Karl Marx, Capital, vol. 1 (Penguin, 1976), 286.
This text is the concluding chapter of Matteo Pasquinelli, The Eye of the Master: A Social History of Artificial Intelligence (Verso, 2023). It has been lightly edited.—Ed.
See the labor process debate: Harry Braverman, Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century (Monthly Review Press, 1974); David Noble, Forces of Production: A Social History of Industrial Automation (Oxford University Press, 1984).
Émile Durkheim, De la division du travail social (Félix Alcan, 1893), translated as The Division of Labor in Society (Free Press, 1984).
Kurt Lewin, “Die Sozialisierung des Taylorsystems: Eine grundsätzliche Untersuchung zur Arbeits- und Berufspsychologie,” Schriftenreihe Praktischer Sozialismus, vol. 4 (1920). See also Simon Schaupp, “Taylorismus oder Kybernetik? Eine kurze ideengeschichte der algorithmischen arbeitssteuerung,” WSI-Mitteilungen 73, no. 3, (2020).
Gaston Bachelard, La dialectique de la durée (Boivin & Cie, 1936), translated as The Dialectic of Duration (Rowman & Littlefield, 2016); Henri Lefebvre, Éléments de rythmanalyse (Éditions Syllepse, 1992), translated as Rhythmanalysis: Space, Time and Everyday Life (Continuum, 2004). Bachelard took the term “rhythmanalysis” from the Portuguese philosopher Lucio Alberto Pinheiro dos Santos.
Frederic Sellet, “Chaîne Opératoire: The Concept and Its Applications,” Lithic Technology 18, no. 1–2 (1993).
Gilles Deleuze, “Postscript on the Society of Control,” October, no. 59 (1992). See also David Savat, “Deleuze’s Objectile: From Discipline to Modulation,” in Deleuze and New Technology, ed. Mark Poster and David Savat (Edinburgh University Press, 2009).
Matthew L. Jones, “Querying the Archive: Data Mining from Apriori to PageRank,” in Science in the Archives, ed. Lorraine Daston (University of Chicago Press, 2017); Matteo Pasquinelli, “Google’s PageRank Algorithm: A Diagram of Cognitive Capitalism and the Rentier of the Common Intellect,” in Deep Search, ed. Konrad Becker and Felix Stalder (Transaction Publishers, 2009).
Irina Kaldrack and Theo Röhle, “Divide and Share: Taxonomies, Orders, and Masses in Facebook’s Open Graph,” Computational Culture, no. 4 (November 2014); Tiziana Terranova, “Securing the Social: Foucault and Social Networks,” in Foucault and the History of Our Present, ed. S. Fuggle, Y. Lanci, and M. Tazzioli (Palgrave Macmillan, 2015).
Grégoire Chamayou, “Pattern-of-Life Analysis,” chap. 5 in A Theory of the Drone (New Press, 2014). See also Matteo Pasquinelli, “Metadata Society,” keyword entry in Posthuman Glossary, ed. Rosi Braidotti and Maria Hlavajova (Bloomsbury, 2018), and “Arcana Mathematica Imperii: The Evolution of Western Computational Norms,” in Former West, ed. Maria Hlavajova and Simon Sheikh (MIT Press, 2017).
Andrea Brighenti and Andrea Pavoni, “On Urban Trajectology: Algorithmic Mobilities and Atmocultural Navigation,” Distinktion: Journal of Social Theory 24, no. 1 (2001).
L. M. Giermindl et al., “The Dark Sides of People Analytics: Reviewing the Perils for Organisations and Employees,” European Journal of Information Systems 33, no. 3 (2022). See also Alex Pentland, Social Physics: How Social Networks Can Make Us Smarter (Penguin, 2015).
The word “statistics” originally meant the knowledge possessed by the state about its own affairs and territories: a knowledge that had to be kept secret. Michel Foucault, Security, Territory, Population: Lectures at the Collège de France 1977–1978, trans. Graham Burchell (Palgrave Macmillan, 2009), 274.
For the influence of brain metrology on the history of AI, see Simon Schaffer: “Judgements that machines are intelligent have involved techniques for measuring brains’ outputs. These techniques show how discretionary behavior is connected with the status of those who rely on intelligence for their social legitimacy.” Schaffer, “OK Computer,” in Ansichten der Wissenschaftsgeschichte, ed. Michael Hagner (Fischer, 2001). On early metrology of the nervous system, see Henning Schmidgen, The Helmholtz Curves: Tracing Lost Times (Fordham University Press, 2014).
Luke Stark, “Algorithmic Psychometrics and the Scalable Subject,” Social Studies of Science 48, no. 2 (2018).
Ruha Benjamin, Race after Technology: Abolitionist Tools for the New Jim Code (Polity, 2019); Wendy Chun, Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition (MIT Press, 2021).
For the imbrication of colonialism, racism, and digital technologies, see Jonathan Beller, The World Computer: Derivative Conditions of Racial Capitalism (Duke University Press, 2021); Seb Franklin, The Digitally Disposed: Racial Capitalism and the Informatics of Value (University of Minnesota Press, 2021).
Henning Schmidgen, “Cybernetic Times: Norbert Wiener, John Stroud, and the ‘Brain Clock’ Hypothesis,” History of the Human Sciences 33, no. 1 (2020). On cybernetics and the “measurement of rationality,” see Orit Halpern, Beautiful Data: A History of Vision and Reason since 1945 (Duke University Press, 2015), 173.
In mechanics, the degrees of freedom (DOF) of a system such as a machine, a robot, or a vehicle is the number of independent parameters that define its configuration or state. Bicycles are usually said to have two degrees of freedom. A robotic arm can have many. A large machine-learning model such as GPT can feature more than a trillion.
Rishi Bommasani et al., On the Opportunities and Risks of Foundation Models, Center for Research on Foundation Models at the Stanford Institute for Human-Centered Artificial Intelligence, 2021 →.
For a different reading of the automation of automation, see Pedro Domingos, The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World (Basic Books, 2015); Luciana Parisi, “Critical Computation: Digital Automata and General Artificial Thinking,” Theory, Culture, and Society 36, no. 2 (March 2019).
“Breaking Models: Data Governance and New Metrics of Knowledge in the Time of the Pandemic,” workshop, Max Planck Institute for the History of Science, Berlin, and KIM research group, University of Arts and Design, Karlsruhe, September 24, 2021 →.
Giorgio Agamben, Where Are We Now? The Epidemic as Politics, trans. V. Dani (Rowman & Littlefield, 2021).
Min Kyung Lee et al., “Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers,” in Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, 2015; Sarah O’Connor, “When Your Boss Is an Algorithm,” Financial Times, September 8, 2016. See also Alex Wood, “Algorithmic Management Consequences for Work Organisation and Working Conditions,” no. 2021/07, European Commission JRC Technical Report, Working Papers Series on Labour, Education, and Technology, 2021.
Redesigning AI, ed. Daron Acemoglu (MIT Press), 2021.
Leigh Phillips and Michal Rozworski, The People’s Republic of Walmart: How the World’s Biggest Corporations Are Laying the Foundation for Socialism (Verso, 2019); Frederic Jameson, Archaeologies of the Future: The Desire Called Utopia and Other Science Fictions (Verso, 2005), 153n22; Nick Srnicek, Platform Capitalism (Polity Press, 2017), 128.
See the websites turkopticon.net, exposing.ai, and politicallymath.in.
Sylvia Wynter, “Towards the Sociogenic Principle: Fanon, Identity, the Puzzle of Conscious Experience, and What It Is Like to Be ‘Black,’” in National Identities and Sociopolitical Changes in Latin America, ed. Antonio Gomez-Moriana, Mercedes Duran-Cogan (Routledge, 2001). See also Luciana Parisi, “Interactive Computation and Artificial Epistemologies,” Theory, Culture, and Society 38, no. 7–8 (October 2021).
Frank Pasquale, New Laws of Robotics: Defending Human Expertise in the Age of AI (Harvard University Press, 2020); Dan McQuillan, “People’s Councils for Ethical Machine Learning,” Social Media+ Society 4, no. 2 (2018).