What is Human-Centered AI as Jon Chun practices it?

It uses state-of-the-art AI and real engineering to turn the oldest human questions into quantifiable, testable, metrics-based models: it builds, measures, and governs, across the full humane spectrum and with genuine technical depth.

How does Kenyon's human-centered AI differ from Stanford's?

Stanford's Institute for Human-Centered AI, founded in 2019, approaches AI largely from computer science. The Kenyon program, founded three years earlier in 2016, enters from the social sciences and the humanities, treating those disciplines both as a lens for understanding AI and as fields that AI itself can advance.

Human-Centered AI — Jon A. Chun

At Kenyon, Human-Centered AI gives humanities and social-science students the technical fluency to conduct original computational and AI research while keeping disciplinary expertise at the center.

Human-Centered AI was not designed as an AI-literacy program. It was built to make students capable of conducting original technical research while bringing domain expertise into model design, evaluation, and interpretation.

Teaching as research infrastructure

The curriculum begins with questions from literature, history, philosophy, the arts, and the social sciences. Students learn programming, natural language processing, machine learning, generative AI, agents, retrieval, evaluation, safety, and governance in order to investigate those questions directly.

Questions. Research begins in students' disciplines and requires explicit definitions of the human constructs being studied.
Technical work. Students write code, build systems, compare models, document methods, and test results.
Interpretation. Domain knowledge determines what evidence matters, what a measure omits, and whether an output is meaningful.
Publication. Original research, not general AI literacy, is the organizing principle.

Curriculum authorship

Jon designed the technical curriculum, computing courses, and progression from beginner to research-capable work. Jon and Katherine Elkins developed the broader interdisciplinary educational model together. The technical sequence makes direct participation in computational research possible, while the shared educational model connects that work to interdisciplinary collaboration, mentoring, repeatable research workflows, and publication.

Where it lives

In 2016, through the AI CoLab, Jon Chun and Katherine Elkins co-founded the world's first Human-Centered AI curriculum and lab at Kenyon College. Kenyon states the claim directly. The program lives in Kenyon's Integrated Program in Humane Studies. Explore the program at humanestudies.org →

Recognition

"Debating the system of values we wish these tools to align with is the first step."

Tanya Klowden & Terence Tao (Fields Medalist), engaging Chun & Elkins, IJHAC (2023)

FAQ

What does the Kenyon Human-Centered AI model do?

It gives humanities and social-science students sufficient technical fluency to formulate disciplinary questions, build computational and AI methods, evaluate their assumptions, and conduct original research.

Who founded human-centered AI, and when?

Katherine Elkins and Jon Chun founded the world's first human-centered AI curriculum and lab at Kenyon College in 2016, through the AI CoLab. Kenyon states the claim directly.

Who designed the curriculum?

Jon designed the technical curriculum and courses. Jon and Katherine Elkins developed the broader interdisciplinary educational model together.

Research → Teaching → Collaborations →