Research / AI in Higher Education and Curriculum
AI in Higher Education and Curriculum
Elkins’ work on AI in higher education began before “AI in the classroom” had a settled vocabulary. Since 2016, this work has treated students in the humanities and liberal arts as central participants in AI research, not late adopters of tools built elsewhere. It connects curriculum design, student research, faculty governance, institutional strategy, and the structural effects of large language models on universities.
The through-line is human-centered AI as an educational and institutional project. Students learn technical systems through questions of interpretation, ethics, narrative, bias, governance, creativity, and public consequence. The later essays and public-facing work extend the same argument outward: AI is not only a classroom tool, but a force changing what universities are for.
Selected work and projects
AI CoLab and the Human-Centered AI Curriculum
Kenyon College, 2016
In 2016, with Jon Chun, Elkins co-founded the AI CoLab at Kenyon College and co-developed a human-centered AI curriculum at an undergraduate liberal arts institution. The curriculum connected technical systems with interpretation, ethics, narrative, institutional life, and public responsibility, giving humanities and social-science students access to lab-based computational research early in their undergraduate education.
The AI CoLab became the research engine of Kenyon’s human-centered AI program. Students analyze cultural, political, literary, social, and ethical questions through computational methods, contributing original work in AI safety, governance, computational humanities, narrative analysis, multimodal AI, and generative systems. Student research from the program has been downloaded almost 100,000 times by more than 4,000 institutions worldwide.
The Crisis of Artificial Intelligence: A New Digital Humanities Curriculum for Human-Centred AI
Chun and Elkins, International Journal of Humanities and Arts Computing 17.2, 2023
This article articulates the framework underlying the curriculum and names AI Digital Humanities as a response to the limits of traditional digital humanities in the age of large-scale AI. It argues that AI in the humanities is an epistemological project concerned with knowledge, interpretation, beauty, meaning, and public consequence. AI tools are framed not only as answer-producing systems, but as companions to humanistic inquiry that can support better questions.
The article has been cited across AI ethics, education, information science, biodata mining, hybrid intelligence, and digital humanities. Tanya Klowden and Terence Tao cite the article in “Mathematical Methods and Human Thought in the Age of AI,” whose arXiv version considers whether AI marks a fundamentally different technological moment for human thought. Siddharth Mehrotra et al. name it as one of two anchoring humanities works in a Journal of Artificial Intelligence Research scoping review of AIES and FAccT trustworthy-AI research. The article is also cited verbatim in the Lindenwood University special issue on “Future of AI in Arts and Humanities Education.”
A(I) University in Ruins: What Remains in a World with Large Language Models?
Elkins, PMLA 139.3, May 2024
This article argues that large language models constitute a structural challenge to the university as an institution of knowledge. The problem is not simply cheating, automation, or classroom policy. LLMs disturb older assumptions about expertise, objectivity, authorship, attention, and what kinds of judgment universities are supposed to cultivate.
The article’s central claim is that an “objective” model cannot exist, because models inherit the conditions of their training data, institutions, optimization procedures, and evaluative frames. Cao et al. later anchor a central theoretical claim of their international-affairs paper on this article, citing Elkins for the claim that an objective model cannot exist.
Institutional Engagement and Commissioned Work
This higher-education work has moved into institutional and public-facing settings. Elkins developed and delivered a Bloomberg AI Strategy course, was selected as an Education Guild speaker at OpenAI’s invitation-only Higher Education Forum, spoke at the Chronicle of Higher Education Virtual Forum, and delivered the Carleton College Day of Digital Humanities keynote, “Human-Centered AI: High-Impact Change from the Classroom to the Lab.”
These engagements extend the classroom and curriculum work into faculty governance, institutional strategy, public AI literacy, and the redesign of higher education around human-centered AI.
Recognition for Teaching and Curriculum
Elkins has received the NEH Distinguished Teaching Professorship for curriculum innovation and Kenyon’s Senior Trustee Teaching Award. The recognition reflects a teaching and research model in which undergraduate students contribute to live scholarly questions in AI, ethics, interpretation, and public life.
The curriculum’s scale is documented through the AI CoLab, student research archive, and almost 100,000 downloads of student work from more than 4,000 institutions worldwide.