AI safety, governance & narrative
Two threads, one practice: evaluating and governing frontier AI, and reading culture computationally. Both treat the humanities as a source of method, not decoration.
AI safety & governance
Co-leading the team representing the Modern Language Association at NIST CAISI (the Center for AI Standards and Innovation), Jon works on LLM evaluation, red-teaming, and ethical auditing. The team's ethics-based audit results were presented during the opening keynote at the consortium's first plenary at the University of Maryland. With collaborators at Oxford and elsewhere he co-authored a comparative study of global AI regulation across the EU, China, and the US (arXiv:2410.21279), and was among the authors of the open-source generative-AI position paper accepted as an ICML 2024 oral presentation.
Computational narrative & digital humanities
Jon and Katherine Elkins were among the first to empirically evaluate GPT-3 for creative writing, and have written on what AI means for Narrative studies and on a human-centered AI curriculum. The work pairs real model evaluation with literary and ethical questions. Several of these threads are co-authored with Elkins; see her research page.
Methods & tools
Recent work extends that narrative-computation thread into open research infrastructure. MultiSentimentArcs, published in Frontiers in Computer Science, proposes a multimodal way to compare sentiment arcs across long-form narrative in film. The related AI-LIT repository was used by Katherine Elkins in her Frontiers article In search of a translator: using AI to evaluate what's lost in translation; that paper is Elkins-authored, so it is treated here as related infrastructure context rather than a Jon-authored selected publication.
Research threads
- NIST CAISI evaluation — LLM evaluation and red-teaming for standards-facing work, with ethical auditing as the through-line.
- Comparative AI regulation — mapping policy approaches across the EU, China, and the US with Christian Schroeder de Witt and Katherine Elkins.
- Computational narrative — from the GPT-3 Writer's Turing Test article to narrative theory, sentiment arcs, and AI-assisted interpretation.
- Open-source generative AI — risks and opportunities of open-source generative AI, including the ICML 2024 position paper.
- Archival Intelligence — applied humane-studies methods for cultural archives, multilingual newspapers, and early jazz artifacts.
Selected publications
- Elkins, K.; Chun, J. (2020). “Can GPT-3 Pass a Writer's Turing Test?” Journal of Cultural Analytics. (Related: AI creativity & co-creation.)
- Chun, J.; Elkins, K. (2022). “What the Rise of AI Means for Narrative Studies.” Narrative 30(1). (Related: sentiment analysis & narrative intelligence.)
- Chun, J.; Elkins, K. (2023). “The Crisis of Artificial Intelligence: A New Digital Humanities Curriculum for Human-Centred AI.” IJHAC 17(2). (Related: AI in higher education & curriculum.)
- Chun, J.; Elkins, K. (2023). “eXplainable AI with GPT-4 for Story Analysis and Generation.” Int. J. Digital Humanities 5(2). (Related: sentiment analysis & narrative intelligence.)
- Chun, J. (2024). “MultiSentimentArcs: a novel method to measure coherence in multimodal sentiment analysis for long-form narratives in film.” Frontiers in Computer Science 6. doi:10.3389/fcomp.2024.1444549
- Eiras, F.; et al. incl. Chun, J., Elkins, K. (2024). “Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI.” ICML (oral). (Related: AI governance & public AI.)
- Chun, J.; Schroeder de Witt, C.; Elkins, K. (2024). “Comparative Global AI Regulation: EU, China, and the US.” arXiv:2410.21279. (Related: AI governance & public AI.)
Related infrastructure
AI-LIT is an open repository for literary AI workflows. Elkins's In search of a translator article in Frontiers in Computer Science used the repository for text processing and visualizations. doi:10.3389/fcomp.2024.1444021
Reception
The reception is strongest when described as specific scholarly uptake rather than as a generic citation count:
- The GPT-3 creative-writing paper was cited by Floridi and Chiriatti in Minds and Machines, by Spitale and co-authors in Science Advances, and by Mei and co-authors in PNAS.
- The Narrative article on AI and narrative studies was later discussed by James Phelan in Poetics Today.
- The human-centered AI curriculum article was cited by Jaramillo and Chiappe in Prospects, and by Tanya Klowden and the mathematician Terence Tao in a 2026 preprint.
- The ICML open-source generative-AI position paper was cited by Taeihagh in Policy and Society.
- The comparative AI regulation paper was cited by Floridi and Ascani in Minds and Machines, by Perboli and co-authors in Economic and Political Studies, and by Olugbade in Global Public Policy and Governance.
What does Jon Chun research?
AI safety, governance, and evaluation — LLM red-teaming and ethical auditing at NIST CAISI, and comparative global AI regulation — alongside computational narrative across the humanities.
What is his role at NIST CAISI?
He co-leads the team representing the Modern Language Association at the NIST Center for AI Standards and Innovation, working on LLM evaluation and red-teaming.
Where has the research appeared?
Venues including ICML (a 2024 oral presentation), the Journal of Cultural Analytics, Narrative, and the International Journal of Humanities and Arts Computing.