Understanding Science with Large Language Models?: Potentials for the History, Philosophy, and Sociology of Science (Science Studies) - Softcover

Softcover

ISBN 10: 3837679942 ISBN 13: 9783837679946

Verlag: transcript, 2026

Inhaltsangabe

How are large language models (LLMs) changing research in the history, philosophy, and sociology of science (HPSS)? The contributors to this volume show how these tools open new possibilities for interpretative scholarship while posing fresh challenges for fields that thrive on qualitative methods, nuance, and historical depth. In essays, dialogues, and provocations, they capture a field in motion at a pivotal moment, driven by the rise of AI. These insights speak not only to HPSS scholars but also to readers across the humanities, social sciences, and AI-related fields, positioning HPSS as a bridge for understanding and shaping how LLMs enter research and society.

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Über die Autorinnen und Autoren

Adrian Wüthrich is a guest professor for the History and Philosophy of Modern Science at Technische Universität Berlin. He leads the project Network Epistemology in Practice (NEPI), funded by a European Research Council Consolidator Grant, which investigates collective knowledge generation in large collaborations. His earlier work addressed interpretational debates in quantum mechanics, the role of images in science, causal reasoning in discovery processes, and the history of concepts in physics. His research often combines historical, philosophical, and computational approaches.

Michael Zichert is a PhD candidate in the project Network Epistemology in Practice at Technische Universität Berlin, where he studies how scientific knowledge is produced in large-scale collaborations. He holds a BA in History of Science from Technische Universität Berlin and an MA in Digital Humanities from Universität Leipzig. His research combines computational methods with the history of science, focusing on diachronic semantic change, social network analysis, and the application of large language models in the field.

Gerd Graßhoff is a professor for the History of Ancient Science at Humboldt-Universität zu Berlin and former director of the Excellence Cluster Topoi. He pioneered computational approaches to the history of science, applying machine learning and causal reasoning to ancient astronomical texts and scientific discovery processes. A Max Planck Fellow and member of Deutsche Akademie der Naturforscher Leopoldina, his research spans from Babylonian astronomy to digital humanities and AI methods for historical research.

Rezensionen

»A cornucopia of ideas for the use of LLMs in HPSS research.« ― Grit Laudel, Technische Universität Berlin

»This volume exemplifies why collaborations between disciplines matter.« ― Martin Potthast, Universität Kassel, and Benno Stein, Bauhaus-Universität Weimar

Details zur Ausgabe

• Verlag: transcript
• Erscheinungsdatum: 2026
• Sprache: Englisch
• ISBN 10: 3837679942
• ISBN 13: 9783837679946
• Einband: Taschenbuch
• Anzahl der Seiten: 522
• Herausgeber: Simons Arno, Wüthrich Adrian, Zichert Michael, Graßhoff Gerd
• Kontakt zum Hersteller: transcript Verlag, Roswitha Gost & Dr. Karin Werner GbR; live@transcript-verlag.de; ; Hermannstraße 26; Bielefeld; 33602; Deutschland