Feature Article
Compulsion Beyond Fairness: Towards a Critical Theory of Technological Abstraction in Neural Networks
Abstract: In the field of applied computer research, the problem of the reinforcement of existing inequalities through the processing of “big data” in neural networks is typically addressed via concepts of representation and fairness. These approaches, however, tend to overlook the limits of the liberal antidiscrimination discourse, which are well established in critical theory. In this paper, I address these limits and propose a different framework for understanding technologically amplified oppression departing from the notion of “mute compulsion” (Marx), a specifically modern form of power based on the social abstraction of wage labor in market exchange. I begin with a reconstruction of the process of technological abstraction in automated pattern recognition, after which I summarize the conceptional shortcomings of representational fairness discourse. In contrast, I demonstrate how the social reproduction of exploitation is conceptualized in critical theory as being mediated through a process of social abstraction, defined as a social practice of reification that manifest in fetishization. To avoid economistic shortcomings, I contextualize the argument of social abstraction against the backdrop of social reproduction theory, which takes the juncture of various historical forms of oppression into account. I conclude by elaborating how technological abstraction corresponds to the problem of mute compulsion by replicating processes of social abstraction.
Leonie Hunter. 2024. “Compulsion Beyond Fairness: Towards a Critical Theory of Technological Abstraction in Neural Networks.” AI & Society. https://doi.org/10.1007/s00146-024-02035-6.
Selected Resources
Adams, R. 2025. The New Empire of AI: The Future of Global Inequality. Cambridge, UK: Polity.
Amaro, R. 2022. The Black Technical Object: On Machine Learning and the Aspiration of Black Being. Cambridge, MA: MIT Press.
Birch, K. and F. Muniesa (eds). 2020. Assetization: Turning Things into Assets in Technoscientific Capitalism. Cambdridge, MA: MIT Press.
Butollo, F. and S. Nuss. 2022. Marx and the Robots: Networked Production, AI and Human Labour, translated by Jan-Peter Herrmann with Nivene Raafat. London: Pluto Press.
Burrell, J., and J. Metcalf. 2024. “Introduction for the Special Issue of “Ideologies of AI and the Consolidation of Power”: Naming Power.” First Monday 29, no.4. https://doi.org/10.5210/fm.v29i4.13643.
Crawford, K. 2021. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press.
Daum, T. 2022. “Artificial Intelligence as the Latest Machine of Digital Capitalism – For Now.” In Marx and the Robots: Networked Production, AI and Human Labour, edited by Florian Butollo, Sabine Nuss and Jan-Peter Herrmann; translated by Jan-Peter Herrmann with Nivene Raafat. London: Pluto Press.
Dean, J. 2024. “The Neofeudalising Tendency of Communicative Capitalism.” TripleC: Communication, Capitalism & Critique 22, no.1: 197-207. https://doi.org/10.31269/triplec.v22i1.1460.
Dyer-Witheford, N., A. M. Kjosen, and J. Steinhoff. 2019. Inhuman Power: Artificial Intelligence and the Future of Capitalism. London: Pluto Press.
Ferrari, F. and F. McKelvey. 2022. “Hyperproduction: A Social Theory of Deep Generative Models.” Distinktion: Journal of Social Theory 24, no.2: 338–360. https://doi.org/10.1080/1600910X.2022.2137546.
Fehrle, J., M. Lieber, and J. J. Ramirez, J. 2024. (De)Automating the Future: Marxist Perspectives on Capitalism and Technology. Brill, 2024.
Fuchs, C.. 2024. “Critical Theory Foundations of Digital Capitalism: A Critical Political Economy Perspective.” TripleC: Communication, Capitalism & Critique 22, no.1: 148-196. https://doi.org/10.31269/triplec.v22i1.1454.
Fuchs, C. 2022. Digital Fascism. Media, Communication and Society Volume Four. New York: Routledge.
Eubanks, V. 2018. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. St. Martin’s Press.
Giblin, R. and C. Doctorow. 2022. Chokepoint Capitalism: How Big Tech and Big Content Captured Creative Labor Markets and How We ’ll Win Them Back. Boston: Beacon Press.
Gilbert, J. and A. Williams. 2022. Hegemony Now: How Big Tech and Wall Street Won the World (and How We Win It Back). London: Verso.
Gray, Mary L. and Suri Siddharth. 2019. Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Boston, MA, USA: Houghton Mifflin Harcourt.
Hampton, L. M. 2023. “Techno-Racial Capitalism: A Decolonial Black Feminist Marxist Perspective.” In Feminist AI: Critical Perspectives on Algorithms, Data, and Intelligent Machines, edited by Jude Brown, Stephen Cave, Eleanor Drage, and Kerry McInerney. Oxford: Oxford UP (online edn, Oxford Academic, 23 Nov. 2023). https://doi.org/10.1093/oso/9780192889898.003.0008.
Halpern, O. 2021. “Planetary Intelligence.” In The Cultural Life of Machine Learning: An Incursion Into Critical AI Studies, edited by J. Roberge and M. Castelle. London: Palgrave Macmillan. https://doi.org/10.1007/978-3-030-56286-1.
Halpern, O. 2023. “Neural ‘Freedoms,’ Population, Choice, and Machine Learning.” In Queer Reflections on AI: Uncertain Intelligences (1st ed.), edited by M. Klipphahn-Karge, A.-K. Koster and S Morais dos Santos Bruss. New York: Routledge. https://doi.org/10.4324/9781003357957.
Halpern, O. 2023. “Financializing Intelligence: On the Integration of Machines and Markets.” E-flux Architecture (March). https://www.e-flux.com/architecture/on-models/519993/financializing-intelligence-on-the-integration-of-machines-and-markets/.
Hunter, L. 2024. “Compulsion Beyond Fairness: Towards a Critical Theory of Technological Abstraction in Neural Networks.” AI & Society. https://doi.org/10.1007/s00146-024-02035-6.
Jacobson, B. N. 2023. “Machine Learning and the Politics of Synthetic Data.” Big Data & Society 10, no.1. 10.1177/20539517221145372.
Joque, J. 2022. Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism. New York: Verso.
Lange, E. L. 2022. “‘Voracious Appetite for Surplus Labour’ Understanding the Digital Revolution Through Marx.” In Marx and the Robots: Networked Production, AI and Human Labour, edited by Florian Butollo, Sabine Nuss and Jan-Peter Herrmann; translated by Jan-Peter Herrmann with Nivene Raafat. London: Pluto Press.
Little, B. and A. Winch. 2021. The New Patriarchs of Digital Capitalism: Celebrity Tech Founders and Networks of Power. New York: Routledge.
McKelvey, F. 2021. “The Other Cambridge Analytics: Early ‘Artificial Intelligence’ in American Political Science.” In The Cultural Life of Machine Learning: An Incursion Into Critical AI Studies, edited by J. Roberge and M. Castelle. London: Palgrave Macmillan. https://doi.org/10.1007/978-3-030-56286-1.
Moore, P. V. and J. Woodcock (eds). 2021. Augmented Exploitation: Artificial Intelligence, Automation, and Work. London: Pluto Press.
Nachtwey, O. and S. Schaupp. 2024. “The Valorization of Interactions. Gift Exchange, Power and Value Creation on Digital Platforms.” Big Data & Society 11, no.2. https://doi.org/10.1177/20539517241259639.
Pfeiffer, S. 2022. Digital Capitalism and Distributive Forces. Bielefeld: transcript. https://www.transcript-publishing.com/978-3-8376-5893-4/digital-capitalism-and-distributive-forces/?number=978-3-8394-5893-8.
Ross, L. 2021. “Transhumanism As the Evolution of the Real Subsumption of Labour Under Capital.” New Proposals: Journal of Marxism and Interdisciplinary Inquiry 12, no.1: 89-110. https://ojs.library.ubc.ca/index.php/newproposals/article/view/194419.
Sadowski, J. 2019. “When Data Is Capital: Datafication, Accumulation, and Extraction.” Big Data & Society 6, no.1: 1–12. doi:10.1177/2053951718820549.
Saha, A. 2024. “Theorising Digital Dispossession: An Enquiry into the Datafication of Accumulation by Dispossession.” TripleC: Communication, Capitalism & Critique 22, no.1: 104-123.
Schaupp, S. 2023. “COVID-19, Economic Crises and Digitalisation: How Algorithmic Management Became an Alternative to Automation.” New Technology, Work and Employment 38, no.2: 311–329.
Srnicek, Nick. 2021. “Value, Rent, and Platform Capitalism.” In Work and Labour Relations in Global Platform Capitalism, edited by Julieta Haidar and Maarten Keune. Cheltenham: Edward Elgar.
Stark, L., D. Greene, and A. L. Hoffmann. 2021. “Critical Perspectives on Governance Mechanisms for AI/ML Systems.” In The Cultural Life of Machine Learning: An Incursion Into Critical AI Studies, edited by J. Roberge and M. Castelle. London: Palgrave Macmillan. https://doi.org/10.1007/978-3-030-56286-1.
Steinhoff, James. 2021. Automation and Autonomy: Labour, Capital and Machines in the Artificial Intelligence Industry. Cham, Swizerland: Palgrave Macmillan.
Van Den Meerssche, D. 2022. “Virtual Borders: International Law and the Elusive Inequalities of Algorithmic Association.” European Journal of International Law 33, no. 1: 171–204, https://doi.org/10.1093/ejil/chac007.
West, S. M. 2019. “Data Capitalism: Redefining the Logics of Surveillance and Privacy.” Business & Society 58, no.1: 20–41. https://doi.org/10.1177/0007650317718185.
Zuboff, S. 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York: Public Affairs.