PeopleofSuperintelligence

Researcher

Katherine Elkins

Katherine Elkins is a Kenyon professor whose work connects AI research with literary interpretation and cultural archives. She earned a B.A. at Yale and a Ph.D. at UC Berkeley, and in 2016 she and Jon Chun founded Kenyon’s human-centered AI curriculum and AI CoLab. Her research tested GPT-3’s literary writing, compared models in The Shapes of Stories, and used AI to study translation and open-source governance. In 2025, she became project lead of Archival Intelligence; as of October 2026, she directs Kenyon’s Integrated Program in Humane Studies and co-leads the Modern Language Association team in NIST’s CAISI AI Consortium.

Timeline

  1. By 2016

    Degrees and an AI curriculum

    She holds a B.A. from Yale and a Ph.D. from UC Berkeley. After college, she lives in Paris, Prague and Asia before returning to the United States for graduate study. In 2016, she and Jon Chun found Kenyon’s human-centered AI curriculum and its AI CoLab.

  2. 2020

    A writer’s Turing test

    In 2020, she and Jon Chun publish “Can GPT-3 Pass a Writer’s Turing Test?”, which makes literary imitation and reasoning experimentally comparable.

  3. 2022

    A book and full professorship

    Her 2022 book The Shapes of Stories uses sentiment analysis, compares over three dozen models, and combines model selection with close readings of narrative passages. Kenyon’s trustees approve her promotion to full professor, effective July 1, 2022.

  4. 2023

    An AI curriculum for humanities

    In 2023, she and Jon Chun publish “The Crisis of Artificial Intelligence: A New Digital Humanities Curriculum for Human-Centred AI” in the International Journal of Humanities and Arts Computing. The article outlines a human-centered AI digital humanities curriculum and ways it opens research paths for the humanities and humanistic social sciences.

  5. 2024

    Translation and open-source AI

    In her 2024 study “In Search of a Translator: Using AI to Evaluate What’s Lost in Translation,” she applies stylometry, emotional arcs and multilingual models such as GPT-4o and Mistral to compare translations of Proust’s In Search of Lost Time. She also coauthors “Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI,” an ICML paper that maps risks and benefits of open and closed generative AI and argues for responsible open release.

  6. 2025

    Archival Intelligence in New Orleans

    Schmidt Sciences selects her to lead Archival Intelligence in 2025, a project building an open AI pipeline for endangered New Orleans archives. It uses fragile newspapers, sheet music, letters and recordings to study the emergence of jazz.

  7. 2026

    An ICML spotlight on public AI

    In 2026, she coauthors “If Open Source Is to Win, It Must Go Public,” a position paper accepted as an ICML Spotlight. The paper argues that open-source AI needs public infrastructure and institutions to make models accessible, sustainable and governed in the public interest.

  8. As of October 2026

    Kenyon professor and NIST co-lead

    As of October 2026, she is a professor of comparative literature and humanities and director of Kenyon’s Integrated Program in Humane Studies. She co-leads the Modern Language Association team in the NIST CAISI AI Consortium and serves as a co-principal investigator of Archival Intelligence with Jon Chun.

Career

  1. Since 2016Kenyon CollegeCo-founder, Full Professor
  2. NowNISTCo-lead of Modern Language Association team

Education

  1. Yale UniversityB.A.
  2. University of California, BerkeleyPh.D.

From the biography.

  1. Of 216 AI researchers who entered public life, 83 held advisory seats and 58 took public rolesIncludes NIST. Of 216 AI researchers who entered public life, 83 held advisory seats and 58 took public roles. Another 97 people moved from public careers into AI organizations or research, with 62% of dated records starting from 2020 on.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes NIST. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. Google has the highest combined h-index among AI organizationsIncludes NIST. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  4. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes NIST. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.

Sources and credits

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  1. Katherine Elkins | Kenyon College kenyon.edu. Checked 21 October 2026.
  2. On the record: Katherine Elkins on Artificial Intelligence kenyoncollegian.com. Checked 21 October 2026.
  3. Katherine Elkins — AI researcher katherineelkins.com. Checked 21 October 2026.
  4. The Shapes of Stories cambridge.org. Checked 21 October 2026.
  5. Full Professors | Kenyon College kenyon.edu. Checked 21 October 2026.
  6. The Crisis of Artificial Intelligence: A New Digital Humanities Curriculum for Human-Centred AI digital.kenyon.edu. Checked 21 October 2026.
  7. In search of a translator: using AI to evaluate what’s lost in translation frontiersin.org. Checked 21 October 2026.
  8. Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI proceedings.mlr.press. Checked 21 October 2026.
  9. Schmidt Sciences awards $11M in grants to bring AI to humanities research schmidtsciences.org. Checked 21 October 2026.
  10. Archival Intelligence — Rescuing New Orleans’ Endangered Cultural Legacy archivalintelligenceai.org. Checked 21 October 2026.
  11. If open source is to win, it must go public arxiv.org. Checked 21 October 2026.