c:o/re Fellow 10/26 – 09/27
M. Beatrice Fazi is a philosopher working on computation, technology, and media. Her research addresses the ontologies and epistemologies of contemporary technoscience, focusing on the role of abstraction and thought in relation to the specificity of computational procedures. Alongside numerous articles and book chapters, she is the author of Contingent Computation: Abstraction, Experience, and Indeterminacy in Computational Aesthetics (2018) and co-author of Digital Theory (2025). Her current work theorises representation in computational systems, examining the epistemic implications of algorithmic decision-making and the notion of synthesis in artificial intelligence. She is Associate Professor at the University of Sussex and a Fellow for 2026/27 at the Käte Hamburger Kolleg: Cultures of Research (c:o/re), RWTH Aachen University. She has previously held visiting research positions and fellowships at New York University, the Center for Advanced Internet Studies (CAIS) in Germany, and the Weibel Institute for Digital Cultures at the University of Applied Arts Vienna. She holds a PhD and an MA from Goldsmiths, University of London, and a Laurea in Philosophy from the University of Macerata, Italy.
Double Incommensurability: Computational Representation and the Varieties of Science in AI
This project examines how different epistemic contexts shape the development, conceptualisation, and deployment of artificial intelligence, with particular attention to the representational processes at work in large language models (LLMs). It builds on M. Beatrice Fazi’s work in the philosophy of computation and digital theory, and on what she has called “the computational search for unity”: the processes through which contemporary AI constructs coherent, if imperfect, internal representational realities of its own.
The project starts from a proposition: the question “what is representation in computation?” cannot be answered from a single epistemic standpoint. It poses a double challenge of incommensurability. The first concerns the ontological difference between human and machine ways of representing. These are not variations on a theme but fundamentally distinct processes; computational representation constitutes its own onto-epistemological domain, which cannot be judged by anthropocentric criteria of meaning, understanding, or explanation alone. The second follows from the first: if computational representation is distinctive in this way, then every attempt to theorise it is shaped by the epistemic tools brought to bear on it.
The project articulates this double incommensurability and maps the varieties of computational epistemology across cultural and institutional contexts. It develops theoretical tools for holding incommensurable frameworks in productive tension, without collapsing them into false universalism or retreating into relativism. In doing so, it contributes to the Käte Hamburger Kolleg’s 2026/27 theme of “varieties of science” and offers conceptual resources for AI governance, technical standards, and cross-cultural collaboration in AI development, where what counts as understanding, representation, or bias depends on the framework from which one asks.
Publications (selection)
Fazi, M. B. (2025) A transcendental philosophy of large language models. Philosophy & Digitality, 2(1), pp. 133–149. https://doi.org/10.18716/pd.v2i1.11665
Fazi, M. B. (2024) The computational search for unity: synthesis in generative AI. Journal of Continental Philosophy, 5(1), pp. 31–56. https://doi.org/10.5840/jcp202411652
Fazi, M. B. (2021) Beyond human: deep learning, explainability and representation. Theory, Culture & Society, 38(7–8), pp. 55–77. https://doi.org/10.1177/0263276420966386
Fazi, M. B. (2019) Can a machine think (anything new)? Automation beyond simulation. AI & Society, 34(4), pp. 813–824. https://doi.org/10.1007/s00146-018-0821-0
Fazi, M. B. (2018) Contingent Computation: Abstraction, Experience, and Indeterminacy in Computational Aesthetics. London: Rowman & Littlefield International.