‘Pattern as a Figure of Knowledge’
Interdisciplinary workshop at the Institute for Advanced Study, University of Amsterdam
Date: 28 March, 2025 (10:00-17:00)
limited seats, sign-up via IAS website
Convenors: Stephan Besser (University of Amsterdam; Institute for Advanced Study/UvA) & Flora Lysen (University of Maastricht)
Pattern is a “great keyword of our times,” as literary scholar Franco Moretti observes. In a world where digital technologies of pattern recognition increasingly shape daily life—from smartphone use to medical diagnostics—this statement makes immediate sense. A recent shift towards pattern as a concept and figure of knowledge is also visible across various disciplines and fields of knowledge, including media studies (Berry), the history of cybernetics and data science (Üstün, Geoghegan, Halpern), digital humanities and cultural analytics (Dixon, Manovich), social science (Mondani & Swedberg), cognitive science and literary studies (Hayles, Besser), (medical) image analysis (Lysen, Daston & Galison), design and architecture (Andersen & Salomon) and the history of knowledge more broadly (Bod).
This interdisciplinary workshop aims to initiate a kaleidoscopic exploration of pattern as a figure of knowledge, past and present. It brings together researchers and scholars from diverse fields to examine the history, poetics and epistemology of this concept. Proposed questions for discussion include: What are the conceptual and aesthetic affordances of pattern as a concept, and what are its ideological implications? How does pattern function as a symbolic form, a (proto)concept (Mondani & Swedberg), a hypernym (Üstün, Besser) or a metadisciplinary shifter (Busbea) within and across fields of knowledge? And how can the genealogy and conceptual history of pattern in the natural and human sciences since the late 19th century illuminate its current impact and transformations in the contexts of AI and digital pattern recognition? The workshop aims to identify areas of overlapping interests among the participants and explore possibilities for establishing a research network of scholars interested in pattern as “keyword” (Moretti) in knowledge production and (post)digital culture at large.
- Key publications
Andersen Paul, and David Salomon. “The Pattern That Connects. New York 2010 , here P. 126.” Acadia10: LIFE in:Formation. Eds. Aaron Sprecher, Yesyahahu Shai, and Pablo  Lorenzo-Airoa. New York: , 2010. 125–132.
Apprich, Clemens, et al. Pattern Discrimination. Minneapolis and London: Minnesota UP, 2018. Print.
Berry, David M. “The Postdigital Constellation.” Postdigital Aesthetics. Art, Computation and Design. Eds. David M. Berry and Michael Dieter. Basingstoke: Palgrave MacMillan, 2015. 44–57.
Besser, Stephan. “Binding Brain, Body and World: Pattern as a Figure of Knowledge in Andy Clark’s Work on Predictive Processing.” POROI: Interdisciplinary Journal of Rhetorical Analysis & Invention 17.1 (2022).
Bod, Rens. World of Patterns: A Global History of Knowledge. Baltimore: Johns Hopkins UP, 2022.
Busbea, Larry, D. The Responsive Environment: Design, Aesthetics, and the Human in the 1970s. Minneapolis: Minnesota UP, 2020.
Daston, Lorraine, and Peter Galison. Objectivity. New York: Zone Books, 2010.
Dixon, Dan. “Analysis Tool Or Research Methodology: Is There an Epistemology for Patterns?” Understanding Digital Humanities. Ed. David M. Berry. Basingstoke: Palgrave, 2012. 191–209.
Geoghegan, Bernhard Dionysius. Code: From Information Theory to French Theory. Duke UP, 2023.
Halpern, Orit. Beautiful Data: A History of Vision and Reason since 1945. Duke UP, 2015.
Hayles, N. Katherine. How We Became Posthuman: Virtual Bodies in Cybernetics, Literature and Informatics, 1999.
Lysen, Flora. “Patterns of Pathology in EEG Research: The “Art and Science” of Analyzing Brain Waves in the Mid-Twentieth Century.” Biomedical Visions: Aesthetics, Epistemology and Medical Practice, Max Planck Institute for the History of Science. Alfred Freeborn and Elizabeth Hughes. Hatje Cantz Verlag. Eds. , forthcoming.
Mondani, Hernan, and Richard Swedberg. “What Is a Social Pattern? Rethinking a Central Social Science Term.” Theory and Society 51 (2021): 543–64.
Moretti, Franco. “Pattern and Interpretation.” Stanford Literary Lab Pamphlet 15 (2017).
Schabacher, Gabriele. “AI and the Work of Patterns: Recognition Technologies, Classification, and Security.” Beyond Quantity: Research with Subsymbolic AI. Ed. Andreas, et al. Bielefeld: , 2021. 123–154.
Üstün, Berkay. “Patterns before Recognition: The Historical Ascendance of an Extractive Empiricism of Forms.” Humanities & Social Sciences 11.55 (2024).
Forthcoming publication
Lysen, F. (2025). Patterns of Pathology in EEG Research: The “Art and Science” of Analyzing Brain Waves in the Mid-twentieth Century. In A. Freeborn & E. Hughes (Eds.), Biomedical Visions: Aesthetics, Epistemology and Medical Practice. Hatje Cantz Verlag.
Paper presentation at:
The Future of Public Values in the Algorithmic Society
International conference by AlgoSoc
10 & 11 April 2025, Amsterdam
“Tedious tasks for “motivated housewives” or algorithms: lessons from the promise of automated cervical cancer screening in the Netherlands (1970–1985)”
This paper explores the history of automating medical imaging to enhance our understanding of contemporary developments in AI-supported image interpretation. The focus is on the initial experiments with population-wide cervical cancer screening in the Netherlands (1970–1985), specifically the prospect of automating the interpretation (cyto-analysis) of Pap smears (uitstrijkjes). Around 1970, government officials projected that computer analysis of Pap smears would be feasible within ten years. In the interim, policymakers proposed outsourcing the growing volume of “tedious” analysis tasks to a new workforce of lower-educated and lower-paid “motivated housewives” (as described in a 1973 report), driven by the slogan “women saving women.” Drawing on historical document analysis and oral history interviews with pathologists, I examine the gendered division of labor, the feminization of the ‘invisible technician,’ and contemporaneous concerns about the monotony of automated work. In line with the AlgoSoc conference’s focus on public values, I am particularly interested in how the (ultimately unfulfilled) promises of automated medical image interpretation were sustained in debates about efficiency (“doelmatigheid”) in Dutch healthcare. Historical discussions on the “hidden” costs of scaling up image interpretation provide a critical backdrop to current debates, where big tech companies propose to digitise large (public) pathology slide libraries to generate value through proprietary AI-based analysis applications.