Editors' Choice

Editors’ Choice: Hidden Constellations

Editors’ Summary: This project combines oral history interviews, digital storytelling, and GIS to map Sapphic areas of New York City. The author begins by visualizing all of the bars in NYC, and identifying the four bars that are explicitly lesbian bars. The author encourages the reader to move beyond the idea of bars as the […]

Editors' Choice

Editors’ Choice: Defactoring Pace of Change

Editors’ Summary: This article argues that bespoke code used in digital humanities research should be treated as a core part of scholarly output rather than treated as invisible technical labor. It introduces defactoring, a method of close reading and restructuring, to reveal a project’s underlying computational narrative. The authors demonstrate this approach by unpacking the […]

Editors' Choice

Editors’ Choice: Can AI Replace Social Science Researchers?

Editor’s Summary: This post responds to another viral essay “Academics Need to Wake Up on AI” that argued that academia is in denial about how good Claude Code is at producing the 6,000–8,000 word journal article. The author argues that the peer-reviewed journal article as the primary unit of academic production is likely dead, and […]

Editors' Choice

Editors’ Choice: No More Tools

Editors’ Summary: In this post, the author shows how the rise of AI has made the critical thinking component of using code in DH even more essential. He details his initial explorations using Claude Code to build DH web apps for use in the classroom. This post argues that the old tools of Digital Humanities […]

Editors' Choice

Editors’ Choice: Do all politicians sound the same? Comparing model explanations to human responses

Editor’s Summary: This article considers the bold claim that politicians from different parties really “all sound the same”. It trains an AI model on 20+ years of Finnish parliamentary speeches and compares its guesses about affiliation with that of 438 human readers. It turns out that the system is ‘better’ at telling parties apart. Humans […]

Editors' Choice

Editors’ Choice: More Strategies for Avoiding AI

Editors’ Summary: This post shares some practical ways college instructors can design courses so students are not completely dependent on AI. It highlights grading systems that reward process over product, moving from writing to problem solving to finally reaching a solution. It empowers the students into realising the value of thinking for themselves instead of […]

Editors' Choice

Editors’ Choice: Stories from Black Physicists in Our Collections

Editor’s Summary: Modern sciences in the United States has been a predominately white-dominated workplace. This project at the American Institute of Physics collects oral history interviews from Black and African American physicists. This project addresses the lack of narratives in the history of science, especially physics, from minority communities. The need to record the perspectives […]

Editors' Choice

Editors’ Choice: AI Inverts the Disciplinary Hierarchy

Editors’ Summary: This post questions the perceived hierarchy of disciplines in the university, and argues that the rise of generative AI challenges this hierarchy. He points to how computer science was considered the most lucrative major in the twenty-first century until the automation of coding made possible by AI. He uses the case study of […]

Editors' Choice

Editors’ Choice: The Price of Scale: AI, Ethics, and the Limits of the Humanities

Editor’s Summary: The question of scale is something that has been troubling many humanities disciplines even before the popularization of computational technologies. In the field of DH, we often perceive that there is an additional layer of abstraction between the researcher and subject because of the digital “screen” and scale of analysis that our technological […]