A dancing bear, a colleague, or a sharpened toolbox? The cautious adoption of generative AI technologies in digital humanities research

• URL: http://arxiv.org/abs/2404.12458v3
• Date: Mon, 14 Jul 2025 18:43:30 GMT
• Title: A dancing bear, a colleague, or a sharpened toolbox? The cautious adoption of generative AI technologies in digital humanities research
• Authors: Rongqian Ma, Meredith Dedema, Andrew Cox,
• Abstract summary: The advent of generative artificial intelligence (GenAI) technologies has been changing the research landscape.<n>This article investigates how Digital Humanities (DH) scholars adopt and critically evaluate GenAI technologies for research.
• Score: 1.8434042562191815
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The advent of generative artificial intelligence (GenAI) technologies has been changing the research landscape and potentially has significant implications for Digital Humanities (DH), a field inherently intertwined with technologies. This article investigates how DH scholars adopt and critically evaluate GenAI technologies for research. Drawing on 76 responses collected from an international survey study and 15 semi-structured interviews with DH scholars, we explored the rationale for adopting GenAI tools in research, identified the specific practices of using GenAI tools, and analyzed scholars' collective perceptions regarding the benefits, risks, and challenges. The results reveal that DH research communities hold divided opinions and differing imaginations towards the role of GenAI in DH scholarship. While scholars acknowledge the benefits of GenAI in enhancing research efficiency and enabling reskilling, many remain concerned about its potential to disrupt their intellectual identities. Situated within the history of DH and viewed through the lens of Actor-Network Theory, our findings suggest that the adoption of GenAI is gradually changing the field, though this transformation remains contested, shaped by ongoing negotiations among multiple human and non-human actors. Our study is one of the first empirical analyses on this topic and has the potential to serve as a building block for future inquiries into the impact of GenAI on DH scholarship.

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