Jon A. Chun
The hardest questions about AI can't be answered inside one discipline, one institution, or one sector — so Jon Chun builds the collaborations that cross all of them. For a decade he has co-built Human-Centered AI: turning the oldest human questions into quantifiable, testable models with frontier AI, across academia, industry, and government.
He co-leads the team representing the 25,000-member Modern Language Association at NIST CAISI (LLM evaluation and red-teaming) and is co-PI on Schmidt Sciences HAVI, building open-source AI to rescue endangered cultural archives. With Katherine Elkins he co-founded the world's first Human-Centered AI curriculum and lab at Kenyon (2016), and earlier co-founded and led SafeWeb.
Harder to fool than we are
Instruction-tuned language models are 110–300× more resistant to narrative manipulation than people — measured across healthcare, law, and finance. The systems we worry about being fooled are, on this axis, far harder to fool than we are. Read the research →
Work the field builds on
When FAccT 2025 researchers mapped how the field defines AI "openness," they named the ICML 2024 position paper Jon co-authored — an oral presentation, top 2% of submissions — one of three canonical openness frameworks. Work shipped; work built on. Trace the reception →
Three seats at once
Held at the same time — uncommon at any career stage, and rare from a small liberal-arts college.
Co-leads the team representing the 25,000-member Modern Language Association — the only humanities-led team in the federal AI-safety consortium.
Co-PI on Archival Intelligence — 1 of 23 teams selected worldwide from 600+ applications for the inaugural Humanities and AI Virtual Institute.
Meta Open Innovation AI Research Community; multi-year BWG forums with analysts, investors, and operators — and a deployed multi-agent product in the market.
| Sector ↓ / Mode → | Built | Measured | Governed | Taught |
|---|---|---|---|---|
| Academia | First HCAI curriculum (2016) | SentimentArcs; ICML 2024 oral | Comparative AI regulation | 400+ mentored projects |
| Industry | SafeWeb; 2 US patents | BWG multi-agent product | SafeWeb → Symantec ($26M) | Open materials, 107K+ downloads |
| Government | NIST CAISI red-team tooling | Ethics-based LLM audits | MLA seat at NIST CAISI | Standards working groups |
| Non-profit | Archival Intelligence (New Orleans) | FATE audit (Notre Dame–IBM) | Human-Centered AI Lab | Helix Center AI+Medicine |
Featured: Co-PI on Archival Intelligence — 1 of 23 Schmidt Sciences HAVI teams worldwide from 600+ applications, building open AI to rescue New Orleans' endangered Creole/Cajun newspapers and early jazz artifacts. See the full collaboration map →
Find your way in
Quotable results (the 110–300× robustness paradox), named co-panelists, and where Jon has appeared in the press.
The publication record, the federal + foundation + industry triple, and how the work is cited across 70+ countries.
SafeWeb's $26M exit and first In-Q-Tel investment, two US patents, and a deployed multi-agent product.
A decade of undergraduates doing original AI research, open to every division of the liberal arts.
Built, shipped, and built on
The largest online-privacy service of its era — roughly 2 billion transactions in 8 months. The first security investment from In-Q-Tel, the CIA-affiliated venture fund; two US patents on early SSL / clientless-VPN appliances; acquired by Symantec in 2003 for $26M — 35× trailing revenue. The full venture story →
A multi-agent AI product deployed in the market, built through multi-year BWG Global forums with analysts, investors, and operators — alongside the Meta Open Innovation AI Research Community (since 2023). Frontier research grounded in commercial deployment. See the industry work →
The best 200+ AI CoLab projects on Digital Kenyon — 107,000+ downloads across 4,760 institutions in 198 countries — plus open tooling like SentimentArcs and MultiSentimentArcs (Frontiers in Computer Science, 2024). Inside the AI CoLab →
Work done first
Dates establish priority; the Reception page documents the uptake that followed. Most of the research below is co-authored with Katherine Elkins.
- 1996Co-architected one of the first web-based electronic health record systems at a major US teaching hospital (University of Iowa).
- 2001The first security investment from In-Q-Tel (the CIA-affiliated venture fund), for SafeWeb.
- 2016Co-founded the world's first Human-Centered AI curriculum and lab at Kenyon, with Katherine Elkins; the field's first peer-reviewed account followed in 2023.
- 2019One of the first methodologies for sentiment analysis of narrative — introducing "middle reading," between distant and close reading.
- 2020The first writer's Turing test of a large language model — "Can GPT-3 Pass a Writer's Turing Test?"
- 2024The first ethics-based audit of moral reasoning in deployed LLMs, and the first systematic EU–China–US regulatory comparison after the EU AI Act.
Breadth, quantified
- 3 seatsFederal (NIST CAISI), foundation (Schmidt HAVI), and industry (Meta / BWG) — held at the same time
- Only oneHumanities-led team in the NIST CAISI consortium, representing the 25,000-member MLA
- ICML 2024Oral presentation — top 2% of submissions
- 110–300×How much harder instruction-tuned LLMs resist narrative manipulation than people
- 61% / 90%Women / non-STEM students in the gateway course — broadening who does serious AI work
- 70+Countries where the research is cited (see Reception)
Cited, quoted, and built on
"GPT-3 writes better than many people."
Luciano Floridi & Massimo Chiriatti, Minds and Machines (2020), citing Elkins & Chun's writer's Turing test"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)"The human-centered AI curriculum at Kenyon encompassed the true essence of a liberal arts education: using a wide range of academic disciplines to discuss world-changing contemporary issues."
Raul Romero, Kenyon College Class of 2022- Forbes
- NPR
- Christian Science Monitor
- Al Jazeera
- Chronicle of Higher Education
See full scholarly reception → · See press coverage → · Grants & recognition →
Common questions
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 — what it means to be human, what a good life and a good society are — into quantifiable, testable models: building, measuring, and governing, not only critiquing. It is distinct from human-centered UI/UX design, from non-technical AI-ethics or STS critique, and from low-code digital humanities, and it works through radical collaboration across disciplines, industry, government, and non-profits. Jon co-founded the world's first such curriculum and lab with Katherine Elkins at Kenyon's AI CoLab in 2016.
What does Jon Chun do now?
He co-leads the team representing the Modern Language Association at NIST CAISI (LLM evaluation and red-teaming) and is co-PI on Schmidt Sciences HAVI (Archival Intelligence), one of 23 teams selected worldwide from 600+ applications.
What was SafeWeb?
An internet privacy company Jon co-founded in 2000 and later led as CEO. It received the first security investment from In-Q-Tel, a nonprofit strategic investment firm affiliated with the CIA, and was acquired by Symantec in 2003 for $26 million.
What is the confidence-scoring method for auditing language models?
Introduced in "Informed AI Regulation," it measures how firmly a model commits to a moral judgment versus hesitates — a way to compare normative certainty across models. It has since been applied across 1,613 social-decision scenarios (COLING 2025) and included among 69 foundational works in the AAAI 2026 "Beyond Verdicts" survey. It is co-authored with Katherine Elkins.