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Audiovisual . 2024
License: CC BY
Data sources: ZENODO
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Audiovisual . 2024
License: CC BY
Data sources: Datacite
ZENODO
Audiovisual . 2024
License: CC BY
Data sources: Datacite
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"Wissen schaffen (lassen!?)". Workflows mit Generativer KI in den Digital Humanities

Authors: Pollin, Christopher;

"Wissen schaffen (lassen!?)". Workflows mit Generativer KI in den Digital Humanities

Abstract

Die rasante Entwicklung von generativen KI-Technologien stellt eine bedeutende Veränderung für die Forschungspraxis nicht nur in den Digital Humanities dar. Dieser Vortrag untersucht den Einsatz von GPT-4-Tier LLM (Gemini Advanced und Claude 3) sowie deren Möglichkeiten und Grenzen in verschiedenen Forschungsprojekten der Digital Humanities. Der Fokus liegt dabei auf Workflows wie der Datenerfassung, Transkription, Übersetzung, Datenmodellierung, Datengenerierung oder -analyse sowie der Visualisierung geisteswissenschaftlicher Daten. Anhand ausgewählter Fallstudien wird die Integration von generativer KI in diese Prozesse dargestellt, wobei sowohl die Automatisierung von Standardaufgaben als auch die Unterstützung komplexerer, analytischer und anspruchsvoller Tätigkeiten wie Datenmodellierung thematisiert werden. Haben generative KI-Modelle, wenn sie im Einklang mit menschlicher Expertise und komplementären Systemen eingesetzt werden, das Potenzial, die Effizienz und Tiefe (digitaler) geisteswissenschaftlicher Forschung zu steigern? Die Studie betont auch die Notwendigkeit, die Grenzen und Herausforderungen, wie die Abhängigkeit von großen Technologieunternehmen beim Einsatz von generativer KI in den Digital Humanities kritisch zu hinterfragen.

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Keywords

Artificial intelligence, Automation, generative technology, Digital humanities, data modeling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average