Essays, talks & public thinking
Jon Chun writes about what technical change asks of people and institutions: how AI alters judgment, education, work, governance, security, and participation in technological research.
Technology in its human setting
Jon Chun's public writing treats AI as a human and institutional problem as well as a technical one. Across essays on programming, education, open models, geopolitics, and deployment, he asks who can participate, which forms of judgment remain necessary, and how institutions should respond when technical capability changes faster than their habits.
This page is deliberately selective. It presents durable public arguments rather than a complete archive of product commentary. For peer-reviewed scholarship, publications, and methods, see Research →.
Essays & public thinking
Eight essays tracing a consistent concern: technical change matters most when it reshapes judgment, institutions, education, work, and public responsibility.
Talks & conversations
Public and institutional conversations in which technical questions are placed alongside questions of judgment, governance, education, and use.
An oral presentation on how access, transparency, innovation, misuse, and governance interact in open-source generative AI. Read the paper →
A Technology Ethics Forum presentation on evaluating fairness, accuracy, transparency, and explainability in LLM reasoning about juvenile recidivism.
AgenticSimLaw uses a simulated juvenile courtroom to examine how multi-agent systems argue, disagree, and explain decisions.
A New York roundtable connecting model behavior and language technology to questions about emotion, interpretation, and human experience.
A faculty conversation about how generative AI changes teaching, authorship, assessment, and the responsibilities of a liberal-arts institution.
Talks on natural-language generation and storytelling with early transformer models, followed by work on prompt-engineered visual narrative generation.