Digital Humanities

The fields of digital scholarship and digital humanities have been using artificial intelligence (AI)-based tools for years. Digital humanists have used methods such as natural language processing, sentiment analysis, and topic modeling to uncover patterns in text-based corpora, for example, since researchers began using computers to aid in their scholarly endeavors.

Generative AI technologies can be used to assist with data annotation, translation and transcription, metadata enhancement, collection curation, text recognition, image analysis and structure recognition of historical documents, text analysis, and coding.

Researchers should be wary of generative AI in relation to data privacy, intellectual property, originality and authorship, research integrity, and how racial and gender bias and discrimination affect the training of generative AI tools. Remember that these generative AI tools are "black boxes" and that oftentimes the processes by which these tools generate information are not transparent.

As Cameron Blevins notes, digital humanists should use these tools and "keep the human in the loop." This sentiment aligns with other scholars' ideas of "co-intelligence" or "hybrid intelligence" in which generative AI is seem as a collaborator along with the researcher. Researchers are able to identify and analyze subtle details and connections that are not obvious to computers, and can recognize what is meaningful or surprising.

Resources

• American Historical Association, Artificial Intelligence and Its Implications for the Present and Future of Historical Research
• Cameron Blevins, A Large Language Model Walks Into an Archive...
• Benjamin Breen, How to Use Generative AI for Historical Research
• Meredith Dedema and Rongqian Ma, The Collective Use and Perceptions of Generative AI Tools in Digital Humanities Research: Survey-Based Results
• R. Darrell Meadows and Joshua Sternfeld, Artificial Intelligence and the Practice of History: A Forum
  • Benjamin Schmidt, Representation Learning
  • Lauren Tilton, Relating to Historical Sources
  • Matthew L. Jones, AI in History
  • Kate Crawford, Archeologies of Datasets
  • Joshua Sternfeld, AI-as-Historian
  • Meredith Broussard, The Challenges of AI Preservation
  • Leen-Kiat Soh et. al., Applying Image Analysis and Machine Learning to Historical Newspaper Collections