Kommers, C., Ahnert, R., Antoniak, M. et al. (35 more authors) (2026) Computational hermeneutics: evaluating generative AI as a cultural technology. Frontiers in Artificial Intelligence, 9. 1753041. ISSN: 2624-8212
Abstract
Generative AI (GenAI) systems are increasingly recognized as cultural technologies, yet current evaluation frameworks often treat culture as a variable to be measured rather than fundamental to the system's operation. Drawing on hermeneutic theory from the humanities, we argue that GenAI systems function as "context machines" that must inherently address three interpretive challenges: situatedness (meaning only emerges in context), plurality (multiple valid interpretations coexist), and ambiguity (interpretations naturally conflict). We present computational hermeneutics as an emerging framework offering an interpretive account of what GenAI systems do, and how they might do it better. We offer three principles for hermeneutic evaluation—that benchmarks should be iterative, not one-off; include people, not just machines; and measure cultural context, not just model output. This perspective offers a nascent paradigm for designing and evaluating contemporary AI systems: shifting from standardized questions about accuracy to contextual ones about meaning.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 Kommers, Ahnert, Antoniak, Benetos, Benford, Bunz, Caramiaux, Concannon, Disley, Dobson, Du, Duéñez-Guzmán, Francksen, Gius, Gray, Heuser, Immel, So, Leigh, Livingston, Long, Martin, Meyer, Mihai, Noel-Hirst, Ostherr, Parker, Qin, Ratcliff, Robinson, Rodriguez, Sobey, Underwood, Vashistha, Wilkens, Wu, Zheng and Hemment. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | Information and Computing Sciences; Human-Centred Computing |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
| Date Deposited: | 11 Mar 2026 11:07 |
| Last Modified: | 11 Mar 2026 11:07 |
| Status: | Published |
| Publisher: | Frontiers Media SA |
| Refereed: | Yes |
| Identification Number: | 10.3389/frai.2026.1753041 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:238898 |
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