Discussion Topic

The idea of “models” has already come up regularly in our readings and discussions, but with the rapid emergence of particular machine learning models, often glossed as “AI,” over the past few years, it seems worthwhile to spend some time digging into both what we mean by “models” in a humanities context, and how particular models are used in DH research and teaching.

Discussion Prep and Collaborative Notes Document

Core

  • Richard Jean So, “All Models are Wrong” (2017), library link
  • Taylor Arnold, Lauren Tilton, and Annie Berke, “Visual Style in Two Network Era Sitcoms,” Cultural Analytics (2019)
  • Sathvika Anand, Quinn Dombrowski, and Xanda Schofield, DSC /#20: Xanda Rescues the Topic Model Disaster (2023), external link
  • Ted Underwood, “Mapping the Latent Spaces of Culture” (2021), external link
  • Kent K. Chang, Mackenzie Cramer, Sandeep Soni, and David Bamman, “Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4” (2023), external link

Penumbra

  • Kate Crawford and Vladan Joler, “Anatomy of an AI System: The Amazon Echo As An Anatomical Map of Human Labor” (2018), external link
  • Julia Flanders and Fotis Jannidis, “Data Modeling in a Digital Humanities Context” in The Shape of Data in Digital Humanities (2018), library link
  • Jonathan D. Fitzgerald and Ryan Cordell, “Classifying Vignettes, Modeling Hybridity,” from Going the Rounds (2019), external link
  • Eun Seo Jo and Timnit Gebru, “Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning”(2020), external link
  • Ryan Cordell, “Machine Learning + Libraries: A Report on the State of the Field” (2020), external link
  • Elizabeth Callaway, Jeffrey Turner, Heather Stone, and Adam Halstrom, “The Push and Pull of Digital Humanities: Topic Modeling the What Is Digital Humanities? Genre” (2020), external link
  • Sandeep Soni, Lauren F. Klein, and Jacob Eisenstein, “Abolitionist Networks: Modeling Language Change in Nineteenth-Century Activist Newspapers” (2021), external link
  • Lauren M. E. Goodlad and Samuel Baker, “Now the Humanities Can Disrupt ‘AI’” (2023), external link
  • Heather Froehlich, “What Do Librarians Need to Know About Quantiative Methods in Digital Humanities?” in Digital Humanities in the Library (2024), library link
  • Peiqi Sui, Eamon Duede, Sophie Wu, and Richard Jean So, “Confabulation: The Surprising Value of Large Language Model Hallucinations” (2024), external link
  • Laura Manrique-Gómez, Tony Montes, and Rubén Manrique, “Historical Ink: 19th Century Latin American Spanish Newspaper Corpus with LLM OCR Correction” (2024), external link

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