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
As principal investigator for the Modern Language Association at NIST CAISI (the Center for AI Standards and Innovation), Jon works on LLM evaluation, red-teaming, and ethical auditing. 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.
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. doi:10.22148/001c.17212
- Chun, J.; Elkins, K. (2022). “What the Rise of AI Means for Narrative Studies.” Narrative 30(1). doi:10.1353/nar.2022.0005
- Chun, J.; Elkins, K. (2023). “The Crisis of Artificial Intelligence: A New Digital Humanities Curriculum for Human-Centred AI.” IJHAC 17(2). doi:10.3366/ijhac.2023.0310
- Chun, J.; Elkins, K. (2023). “eXplainable AI with GPT-4 for Story Analysis and Generation.” Int. J. Digital Humanities 5(2). doi:10.1007/s42803-023-00069-8
- 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).
- Chun, J.; Schroeder de Witt, C.; Elkins, K. (2024). “Comparative Global AI Regulation: EU, China, and the US.” arXiv:2410.21279
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.
- 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 is principal investigator for 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.