Affiliated Departments & Programs

Katherine Elkins works in both applied and theoretical humanities and social sciences with a focus on artificial intelligence, emotion, cognition, linguistics, ethics, and storytelling. She has published in both traditional humanities journals like Poetics Today, Narrative, PMLA, MLN, Philosophy and Literature and MLQ as well as in computing venues like Proceedings of ICML, Frontiers of Computer Science, the Journal of Cultural Analytics, the International Journal of Digital Humanities and the International Journal of Humanities and Arts Computing. She is the editor of Oxford University Press’s "Philosophical Approaches to Proust’s In Search of Lost Time" and author of "The Shapes of Stories: Sentiment Analysis for Narrative" (Cambridge UP), in which she developed the first methodology to surface emotional arc for narrative. 

In 2016 she co-developed the first human-centered AI curriculum and co-founded Kenyon’s AI Lab. Recipient of Kenyon’s Senior Trustee Teaching Award, she was awarded an NEH Teaching Professorship for curriculum innovation and became one of the first in the world to advocate for leveraging AI in the service of humanities and social science research. Since then she has given over a dozen keynotes and appeared in various media outlets, where she talks about both the risks and opportunities of generative AI. 

She is a member of Meta’s Open Innovation AI Research Community, the multi-national group Public AI, Women in AI, and AI in Education. She has also served as co-PI representing the Modern Language Association for the U.S. AI Safety Institute and for the IBM/Notre Dame Tech Ethics Lab. Her passion is supporting voices in AI and computing that are typically underrepresented, and she has mentored over 300 AI/ML student research projects that have been downloaded tens of thousands of times from digital Kenyon by over a thousand institutions in over one hundred countries. 

Areas of Expertise

Human-centered AI, Multimodal and Multilingual Generative AI, Affective AI, Narrative, Translation, Explainable AI, Bias and Fairness, AI Regulation, AI Ethical Auditing and AI Safety

Education

2002 — Doctor of Philosophy from Univ. of California Berkeley

1990 — Bachelor of Arts from Yale University

Courses Recently Taught

Centered on the big questions emerging from the rise of big data and AI, this course offers an interdisciplinary, humanities-centered introduction to programming and data analysis. As part of the new data humanities movement, our focus is on telling the stories we find in data, exploring how to count what counts and critically quantifying issues of bias and representation. With hands-on projects like analyzing Netflix data and exploring the Twitterverse, we also build the foundation for topics covered more fully in intermediate courses: natural language processing, social network models, and machine learning and artificial intelligence. No prerequisite.

Cultural analytics is the study of culture using diverse sources and data-driven methods. We analyze language from texts to tweets and social networks from film to the Twitterverse. In this project-based course, students code ways to explore phenomena like the social networks in "Game of Thrones" and the classification of tweets as Trump or Trudeau. They apply what they have learned for a final project of their choice. Students new to coding should contact the instructor for information on how to complete a self-paced mini coding course before the start of the semester. This course does not count toward the completion of any diversification requirement. No prerequisite. Offered every other year.

This course is an interdisciplinary, humanities-centered coding course that explores the philosophical and ethical questions raised by AI. Ethical questions include issues of bias, fairness and transparency, as well as AI-human value alignment. We explore AI as a mirror of both our best and worst natures: how it can surveil, disemploy and police, but also play games, write text, create images and compose music. Prerequisite: any IPHS course.

This course, designed as a research and/or studio workshop, allows students to pursue their own interdisciplinary projects. Students are encouraged to take thoughtful, creative risks in developing their ideas and themes. Those engaged in major long-term projects may continue with them during the second semester. This course does not count toward the completion of any diversification requirement. No prerequisite. Junior standing.

Individual study in the Integrated Program in Humane Studies is reserved for juniors and seniors who have completed at least one course in the program. Individual study projects are designed to offer the opportunity for directed reading and research in areas not generally covered by the regular offerings of the program, or by the regular offerings of other programs or departments. Alternatively, such projects may offer the opportunity for more advanced research in areas already addressed in program offerings. In some instances, they may offer the possibility of studying languages not otherwise available, or not available at an advanced level, in the College curriculum (e.g., Old Icelandic, Old English). Students undertaking an individual study project are expected to meet with their advisors on a regular basis, ordinarily at least once a week. Individual study projects are expected to embody a substantial commitment of time and effort, which, at the discretion of the project advisor, may result in a major essay or research report. Students wishing to undertake such a project should first gain, if possible a semester in advance, the permission of a potential advisor or mentor and then submit a written prospectus of the project for the approval of both the prospective advisor and the program director. Because students must enroll for individual studies by the end of the seventh class day of each semester, they should begin discussion of the proposed individual study by the semester before, so that there is time to devise the proposal and seek departmental approval. This course does not count toward the completion of any diversification requirement.