Publications & selected work

Books

• Elkins, K. (2022). The Shapes of Stories: Sentiment Analysis for Narrative. Cambridge University Press.
• Elkins, K., ed. (2022). Proust's In Search of Lost Time: Philosophical Perspectives. Oxford University Press.

AI Safety & Evaluation

• Two papers under review at AIES 2026 (cross-cultural ethical auditing of frontier models). Titles withheld pending double-blind review.

For peer-reviewed work on model evaluation, red-teaming, negation sensitivity, and ethical reasoning, see the scholarly profiles above.

AI Governance & Policy

• Comparative research on AI regulation in the European Union, China, and the United States, including open-model governance and institutional accountability.
• Elkins, Katherine. “The MLA’s Work on Federal AI Standards.” MLA Newsletter, vol. 58, no. 2, Summer 2026, pp. 1–2. MLA-member access.

Computational Humanities & Narrative

• Elkins, K., & Chun, J. (2020). "Can GPT-3 Pass a Writer's Turing Test?" Journal of Cultural Analytics.
• Chun, J., & Elkins, K. (2023). "The Crisis of Artificial Intelligence: A New Digital Humanities Curriculum for Human-Centered AI." International Journal of Humanities and Arts Computing.

Cultural Heritage & Archival AI

• Elkins, Katherine. “The Dual Edge: AI’s Impact on Cultural Production and Preservation.” Forthcoming in Artificial Intelligence and Culture: A Global Perspective from Cairo. UNESCO Regional Office for Egypt and Sudan.
  Developed from an invited UNESCO Cairo presentation on Artificial Intelligence and Cultural and Creative Industries, the chapter examines creative labor, cultural diversity, AI safety, and the opportunities AI creates for preserving endangered cultural heritage. It includes early work from the Archival Intelligence initiative on poorly digitized New Orleans cultural materials.

Public Scholarship

• Elkins, Katherine, and Jon Chun. “Provenance Infrastructure as a Safeguard for Cultural Commons in the Age of Generative AI.” Contribution to the AI, IP & Culture Repository co-design process.
  A proposal for provenance infrastructure, rights-aware AI training, cultural-data governance, and digital cultural sovereignty. See the Lab news entry for context.