IPHS Courses

Courses in the Integrated Program in Humane Studies (IPHS) bring the conceptual depth of humanistic training to the quantitative capabilities of AI.

IPHS 200: Programming Humanity

Each week pairs a computational concept with a humanistic question: algorithms and intelligence, data and analogue perception, programming languages and linguistic relativity, networks and social bonds, databases and surveillance, NLP and meaning, machine learning and prediction. Students learn Python, data analysis and critical thinking about what computation can and cannot capture about human experience. Selected student projects are published to Digital Kenyon.

This is an introductory survey course with no prerequisites. It is designed for both humanities students seeking to understand technology and technology-oriented students seeking to understand the larger social and ethical issues surrounding technology.

IPHS 300: AI for Humanity

Built around the many-model approach developed by Kate Elkins and Jon Chun: what are the different kinds of AI, when is each one useful, and what does each reveal about the connections between human and machine intelligence? Students work across traditional machine learning, deep learning, and generative AI, learning not just how each approach works but why it works differently — what it can represent, where it fails, and what those failures tell us. The course develops the judgment to choose the right model for the right question, a capability that purely technical programs do not build. Selected student projects are published to Digital Kenyon.

IPHS 400: Frontiers in Generative AI

Students who understand how AI systems work are ready to build with them. In Frontiers, students move from understanding to creation, completing four projects with the same tools and framework used across industry and research: a chatbot with a distinct personality and memory, a system that uses embeddings to find meaning in data, a knowledge-enhanced application that draws on outside sources to answer complex questions, and a multi-agent AI simulation replicating complex human knowledge workflows. No prior engineering background is required.

Students arrive prepared by IPHS 200 and IPHS 300, and they leave with a portfolio of working projects that demonstrates to graduate schools and employers what a human-centered AI education makes possible. Selected student projects are published to Digital Kenyon.

IPHS 484: Senior Seminar (Capstone)

The capstone research experience for IPHS concentrators. Students design and execute a semester-long original project applying AI methods to questions in the humanities, social sciences, or public interest. Projects take many forms: apps, startup pitches, computational tools, creative works, and entrepreneurial ventures. The seminar is workshop-based, with iterative development, peer feedback, and faculty mentorship guiding each project from concept through completion. Recent work has analyzed 17,000 ChatGPT conversations to study human-AI interaction, built multi-agent AI systems for sports management, developed AI tools for equity research, and investigated private equity's impact on healthcare. All student projects are published to Digital Kenyon.