Impact of AI: Gamechanger for Image Classification in Historical Research?

Michela Vignoli, Doris Gruber, Rainer Simon, Axel Weißenfeld

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

Abstract

AI opens new possibilities for processing and analysing large, heterogeneous historical data corpora in a semi-automated way. The Ottoman Nature in Travelogues (ONiT) project develops an interdisciplinary methodological framework for an AI-driven analysis of text–image relations in digitised printed material. In this paper, we discuss our results from the first project year, in which we explore the potential of multi-modal deep learning approaches for combined analysis of text and image similarity of “nature” representations in historical prints. Our experiments with OpenCLIP for zero-shot classification of prints from the ICONCLASS AI Test Set show the potential but also limitations of using pre-trained contrastive-learning algorithms for historical contents. Based on the results and our learnings, we discuss in which way computational, quantitative methods affect our underlying epistemology stemming from more traditional “analogue” methods. Our experiences confirm that interdisciplinary collaboration between historians and AI developers is important to adapt disciplinary conventions and heuristics for use in applied AI methods. Our main learnings are the necessity to differentiate between distinct visual features in historical images versus representations of “nature” that require interpretation, and to develop an understanding for the features an AI algorithm can be retrained to detect.
OriginalspracheEnglisch
TitelDigitale Methoden in der geschichtswissenschaftlichen Praxis: Fachliche Transformationen und ihre epistemologischen Konsequenzen
UntertitelKonferenzbeiträge der Digital History 2023, Berlin, 23.-26.5.2023
ErscheinungsortBerlin
Seiten1-15
Seitenumfang15
DOIs
PublikationsstatusVeröffentlicht - 2023
VeranstaltungDigital History Tagung - Humboldt-Universität zu Berlin, Berlin, Deutschland
Dauer: 24 Mai 202326 Mai 2023
https://dhistory.hypotheses.org/digital-history-tagung-2023

Konferenz

KonferenzDigital History Tagung
KurztitelDigital History
Land/GebietDeutschland
StadtBerlin
Zeitraum24/05/2326/05/23
Internetadresse

Research Field

  • Ehemaliges Research Field - Data Science

Schlagwörter

  • Artificial Intelligence
  • Computer Vision
  • Book History
  • Image Classification
  • Early Modern Prints

Fingerprint

Untersuchen Sie die Forschungsthemen von „Impact of AI: Gamechanger for Image Classification in Historical Research?“. Zusammen bilden sie einen einzigartigen Fingerprint.

Diese Publikation zitieren