Looking to explore DH-relevant courses–both at Princeton and beyond?

We’ve made a list of graduate courses for fall 2025 offered throughout the Inter-University Doctoral Consortium (IUDC).

With the approval of the certificate director, these courses can be used to satisfy the elective requirement for the CDH’s Graduate Certificate in Digital Humanities.

To enroll in a course, submit a completed registration form to the IUDC coordinator at both your host and home institutions.

Princeton University

IUDC Details

Note: for a list of grad seminars offered or cross-listed by the CDH that automatically count toward the Graduate Certificate in DH, please see Graduate Courses in DH.

Architecture

• ARC 525 / ART 524 / CDH 525: Mapping the City: Cities and Cinema (M. Christine Boyer)
• ARC 546 / URB 546: Technology and the City: The Architectural Implications of Networked Urban Landscape (Andrew Laing)
• ARC 568: Robotic Architecture Workshop (V. Mitch McEwen)

Art and Archaeology

• ART 559: Archive, Cinema, Fabulation (Tina M. Campt)

Computational and Data Humanities

• CDH 507 / HUM 507: Data in the Humanities (Grant R. Wythoff)

Computer Science

• COS 511: Theoretical Machine Learning (Elad Hazan)
• COS 526 / ECE 576: Neural Rendering (Felix Heide)
• COS 534: Fairness in Machine Learning (Lydia T. Liu)
• COS 568: Systems and Machine Learning (Kai Li)
• COS 583 / ECE 583: Great Moments in Computing (Margaret R. Martonosi)
• COS 598B: Advanced Topics in Computer Science: Formal methods with-and-for machine learning (Aarti Gupta)
• COS 598I: Advanced Topics in Computer Science: Modern Data Systems (Jialin Ding)

East Asian Studies

• EAS 509 / CDH 509: Text Analysis in a CJK World (Paul A. Vierthaler)

History of Science

• HOS 599 / HIS 599 / CDH 599: Special Topics in the History of Science, Technology, and Medicine: Information-Computing-Infrastructure (Matthew L. Jones)

Music

• MUS 561: Music Cognition Lab (Elizabeth H. Margulis)

Philosophy

• PHI 543 / SML 543: Machine Learning: A Practical Introduction for Humanists and Social Scientists (Sarah-Jane Leslie)

Politics

• POL 506 / SPI 595: Qualitative Methods (Corrine M. McConnaughy)
• POL 572: Quantitative Analysis I (Zeyang Yu)
• POL 573: Quantitative Analysis II (Marc Ratkovic)
• POL 574: Quantitative Analysis IV (Arthur Spirling)

Public and International Affairs

• SPI 528D: Topics in Domestic Policy: Policymaking and Ethical Challenges from Advances in Science & Tech (Zeynep Tufekci)
• SPI 585A: Topics in STEP: Societal Impacts of Data, Algorithms and AI (Aleksandra Korolova)

Sociology

• SOC 504: Advanced Social Statistics (Sam Trejo)
• SOC 505: Research Seminar in Empirical Investigation (Yu Xie)

Statistics and Machine Learning

• SML 510: Graduate Research Seminar (Sarah-Jane Leslie)

Columbia University

IUDC Details

Anthropology

• GR6075: Power and Technoaesthetics (Rosalind Morris)

Center for the Study of Ethnicity and Race

• GU4004: Data, Race, Power and Justice (Brian Luna Lucero)

Comparative Literature & Society

• GU4545: Wittgenstein in the Machine (Lydia Liu)

Comparative Media

• GR8483: Intro to Comparative Media (Ying Qia and Nico Baumbach)

English Theatre Arts

• GU4725: Technologies of Modern Drama (William B Worthen)

European History - Politics

• GU4000: Digital Sovereignty and the European Union (Fabiano Cristiano)

Film

• GU4048: Music, Sound and Image Theory (Jane Gaines and Benjamin A Steege)
• GU4310: Experimental Film & Media (Ronald Gregg)

Institute for Study of Human Rights

• GU4270: Digital Advocacy for Human Rights: Social Media and Open Source Intelligence (Ted Perlmutter)

Music

• GR6601: Interactive Sound & Video (Seth Cluett)

CUNY Graduate Center

IUDC Details

Comparative Literature (see courses)

• CL 86500: Archaeology of Media: Film, Fashion, Montage (Eugenia Paulicelli)

Data Analysis and Visualization (see courses)

• DATA 70600: Special Topics in Computer Fundamentals: AI-Assisted Programming (Stephen Zweibel)
• DATA 71200: Advanced Data Analysis (Howard Everson)
• DATA 73000: Visualization and Design (Julia Bloom)
• DATA 73200: Interactive Data Visualization (Ellie Frymire)
• DATA 74000: Data, Culture and Society (Kevin Ferguson)
• DATA 78000-01: Special Topics: Software Lab Design: Creative Computing (Omar Nema)
• DATA 78000-02: Special Topics: Categorical Data Analysis in Python (Tim Shortell)
• DATA 78000-03: Special Topics: Agentic AI (Michelle McSweeney)
• DATA 78000-04: Special Topics: AI for What?: Developing Critical AI Practices with Mission-Driven Organizations (Kathleen M. Cumisky)

Digital Humanities (see courses)

• DHUM 70002: Digital Humanities: Methods and Practices (Bret Maney)
• DHUM 74500: Digital Pedagogy II: Theory, Design, and Practice (Shawna Brandle)
• DHUM 78000-01: Special Topics: Digital Memories: Theory and Practice
• DHUM 78000-02: Special Topics: Decolonial AI and Digital Humanities: Centering Indigenous, Afro-Diasporic, and Latinx Voices
• DHUM 78000-04: Special Topics: Social Justice and Public Scholarship

English (see courses)

• ENGL 82000: The Appetite of Thought: Exercises in Eco-Techno Criticism & Reading (Joan Richardson)

Interdisciplinary Studies

• IDS 81670: Selected Topics in IDS: More Just Technology: Publics & Futures (Maura Smale and Javiela Evangelista)

Linguistics

• LING 83100: Psycholing / Cognitive Linguistics: Advanced Natural Language Processing (Alla Rozovskaya)

Music ( see courses)

• MUS 83201: Music in / on the Internet (Eliot Bates)

Psychology

• PSY 80103-04: Seminar in Special Topics: Inter-active Digital Narrative Research (Colette Daiute)

New School for Social Research

IUDC Details

Anthropology

• GANT 5201: Documentalities: The Politics of Archives (Anne Stoler)
• GANT 6281: Anthropologies of AI (Sareeta Amrute)
• GANT 6614: Technopolitics (Antina von Schnitzler)

New York University

IUDC Details
(NYU course listings can be accessed here)

Anthropology

• ANTH-GA 1216: Culture and Media II (Tejaswini Ganti)

Digital Humanities and Social Science

• DHSS-GA 1122: Web Development (Jo Suk)
• DHSS-GA 1125: Programming with Data (Allison Parrish)

English 

• ENGL-GA 2912: Philosophy as Literature, Literature as Philosophy: The Essay, from Montaigne to ChatGPT (Robert Young)
• ENGL-GA 2944: The Social Life of Paper (Lisa Gitelman)

Experimental Humanities & Social Engagement

• CEH-GA 1018 007: Data Justice (Toussaint Nothias)

History

• HIST-GA 1011: Digital Archives (Mary Lauren Kidd)

Institute for the Study of the Ancient World

• ISAW-GA 3024: Introduction to Digital Humanities for the Ancient World (Sebastican Heath, Tom Elliott, and Patrick Burns)

Journalism

• JOUR-GA 1182–09: Data Journalism (Meredith Broussard)

Linguistics

• LING-GA 1012: Large Language Models: Evaluation and Applications (Tal Linzen)

Philosophy

• PHIL-GA 3010: Topics in Philosophy of Mind (Ned Block and Andrew Rubner)

Psychology

• PSYCH-GA 2013: Psychology of Social Media
• PSYCH-GA 2040-009: Current Topics: Psychology and Artificial Intelligence

Public Humanities

• PUBHM-GA 1101-003: Case Studies in Public Humanities: The Hemispheric Institute and HIDVL (Ana Dopico and Daniel Howell)

Sociology

• SOC-GA 2316: Introduction to Computational Text Analysis (Bart Bonikowski)
• SOC-GA 3350: Social Data Science Workshop (Bart Bonikowski)

Stony Brook University

IUDC Details
(Stony Brook course listings can be accessed here)

Technology and Society

• EMP 532: Big Data Systems (Firman Firmansyah)

Congratulations to Meredith Martin, Professor of English and Director of the Center for Digital Humanities, who has been selected for a 2025 Humanities and AI Virtual Institute (HAVI) award by Schmidt Sciences.

Professor Martin is part of a grant of up to $450,000 led by Tom Lippincott (Johns Hopkins University) with co-PIs John Hale (Johns Hopkins University) and Robert Lieck (Durham University). The project, "An ML Toolkit to Find Hierarchical Structure in Multi-Modal/Lingual Data," will develop computational methods to analyze structural patterns in poetry, narrative fiction, and music across different languages and historical periods.

The collaboration brings together expertise in literary studies, linguistics, musicology, and machine learning to create tools that both apply AI to illuminate cultural artifacts and draw on humanistic understanding to advance how AI models learn sequential structure. The interdisciplinary team includes researchers from Johns Hopkins University, Princeton University, and Durham University.

About the Project

The research addresses a fundamental challenge: how humans experience and create hierarchical structure in cultural artifacts under cognitive limitations. From poetic meter and narrative patterns to musical form, structure guides creative expression and shapes how we perceive and remember art across time and cultures.

The team will develop a Python library for defining, training, and interpreting sequence models designed to infer hierarchical structure, along with three humanistic case studies examining poetry, language and narrative, and music. Professor Martin will lead the poetry case study, investigating how poetic structures—including form, rhyme, and meter—have been deployed, interpreted, and taught over more than a millennium of English verse. Working with the Chadwyck-Healey English Poetry corpus of 336,180 poems written between 900 CE and the present day, the research will explore questions such as when and where poetic meter is predictably regular or irregular, and how metrical and rhythmic patterns carry meaning across time.

Broader Impact

Schmidt Sciences has awarded $11 million to 23 research teams around the world who are exploring new ways to bring artificial intelligence into dialogue with the humanities, from archaeology and art history to literature, linguistics, film studies, and beyond. As part of the Humanities and AI Virtual Institute (HAVI), these interdisciplinary teams will both apply AI to illuminate the human record and draw on humanistic questions, methods, and values to advance how AI itself is designed and used.

Read more about all 23 awarded projects: https://www.schmidtsciences.org/havi-2025-announcement/

Celebrating the HAVI Community

Beyond celebrating Professor Martin's award, we're thrilled to see so many CDH colleagues and collaborators among this year's 23 HAVI awardees—a testament to the vibrant, interconnected community advancing digital humanities research.

Peter Henderson (Computer Science, Princeton University) is developing "AI for Understanding the Law and its Evolution"—creating AI tools to trace how legal ideas spark, spread, and change across centuries of multilingual, multimodal legal texts.

Jim Casey (UC Santa Barbara) is leading "Communities in the Loop"—developing AI methods to identify veiled protest in 19th-century Black newspapers. Jim is a former CDH postdoc, and we're proud to see his vital work recognized.

Peter Bol (Harvard University), a Princeton PhD alum from 1980, is leading "Augmenting Retrieval for Eurasian Languages"—training multilingual AI models to study Asian-language manuscripts, including low-resource languages like Tibetan, to reduce bias in historical research.

David Bamman (UC Berkeley) is creating Kinolab to bridge large-scale computational analysis with close viewing of film and television. David has been a valued collaborator through our New Languages for NLP initiative, LLM speaker series, and Ends of Prosody event.

Co-investigator, Lauren Tilton (University of Richmond), spoke at CDH in October 2024 on "Distant Viewing: AI and Ways of Seeing" for our Humanities for AI series.

Matthew Wilkens (Cornell) leads "Artificial Intelligence for Cultural and Historical Reasoning" with collaborators including David Mimno (PPA board member), Ted Underwood (Startwords contributor), and Andrew Piper (early Humanities Council visitor through German).

Gregory Crane (Tufts University) is working on "Beyond Translation: Opening up the Human Record." Greg was the very first speaker we invited for the Digital Humanities Initiative back in c. 2012. His collaborator, David Smith, serves on our PPA board and participated in Ends of Prosody.

The CDH’s Humanities for AI initiative, launched in fall 2024, has presented a range of events, projects, and conversations exploring how humanistic values and approaches are crucial to the development, use, and interpretation of the field of AI, including this year’s Modeling Culture program.

Continuing our Q&A series where we share perspectives on the impact of AI on humanities scholarship, we welcomed John Ladd (Assistant Professor, Department of Computing and Information Studies, Washington & Jefferson College) to respond to some questions after his talk in September. In “Human and Machine Intelligence in Networks of Early Modern Print,” he investigated how artificial intelligence and other computational approaches can help us to understand the distant past.

Your work bridges early modern literature and computational methods. How does your research and teaching inform your understanding of “Humanities for AI”?

In my research, I frequently apply computational methods and digital tools to early modern book history and literature. I teach in an interdisciplinary computing program where I show students how to apply humanities methods and objects of study to data science and the history of technology. It’s this back-and-forth exchange, of using technology in the humanities and using the humanities to understand technology, that the digital humanities has long stood for and that can help us frame the humanities’ relationship to AI. Humanities scholars continue to demonstrate the value of interrogating AI ethically, critically, and in historical context, and I believe that we’re starting to see the ways large language models might be used, with sensible guardrails, as research tools as well as research subjects.

In your talk, you noted that human-machine interaction has been happening since letterpress printing itself, using an engraving of an early modern print house to illustrate “the merger of different kinds of expertise” and drawing attention to the human labor behind seemingly “magical” new technologies. How does thinking about this historical precedent shape your approach to contemporary AI tools in humanities research?

I tend to focus on continuities between contemporary AI/large language models and a long history of technological change. The idea that AI is a revolutionary break from all previous technologies is a narrative that serves particular interests. I prefer narratives that put AI and LLMs into social and cultural contexts, like the recent frameworks of “AI as cultural and social technologies” and especially “AI as Normal Technology.” For humanities researchers and everyday users, it’s advantageous to think of AI as part of a long history of text technologies, going back to the printing press and before. This is why I emphasize LLMs’ ties both to decades of work in the digital humanities and to a broader view of the history of technology. This view helps us to see the many layers of human labor that have gone into AI, and the ways AI is still reliant on human expertise, just as other similar text technologies have been.

You’ve worked extensively on building research tools for humanists, from Network Navigator to the EarlyPrint Bibliographia. Now that LLMs have entered the picture, how has the landscape of digital humanities “tool building” changed? What ways have you found to engage with LLMs in your development work, with or beyond the chatbot?

An LLM itself is a new kind of tool, but it’s also a way to make tool-building more accessible and inviting. AI coding assistants can make it less intimidating to build a custom tool or website for a personal research project. There’s still a lot of value, and necessity, in learning how code works and how to make code work for you, but I am hopeful that LLMs will lower the barrier to entry and make the process more inviting. The novelist and experimental coder Robin Sloan has used the phrase “an app can be a home-cooked meal” to describe the empowering process of taking toolmaking into your own hands and building something just for yourself or for a small group. Instead of large-scale apps, these bespoke tools are so often the kinds that researchers really need, and LLMs may open the door for more such tools to be built.

Your work on local LLMs (with Melanie Walsh, et. al.) emphasizes privacy and sustainability for humanities AI research. Can you talk about why running models locally matters for humanistic inquiry? What are the technical and ethical considerations that led you to focus on this approach?

It’s essential for humanities researchers to find ethical ways of working with LLMs that respond to the many valid critiques of this technology. Working with LLMs locally reduces their environmental impact. Instead of processing your query at a massive data center, your own regular computer hardware can run the task, saving water and energy. The prompt and data also never leave your computer, making the whole interaction more private and avoiding corporate interests. While not every humanities research task can be run this way, many of the datasets and research questions that humanists use are at a scale that can be processed by a local LLM. The local models give you more control over the entire process, and they make the task more replicable in order for the work to be verified and reviewed. Both technically and ethically, I think local LLMs are a great path forward for many folks who want to work with this technology, and I’m working to make sure more people know this is an option!

In the case study you presented, examining whether early modern printers produced books on the same subjects over their careers, you combined text classification, network analysis, and data visualization. What did machine learning reveal that traditional bibliographic methods might have missed—and vice versa? How does a “mesoscopic” approach help you navigate moments where computational and analog approaches yield different insights?

Many early modern book historians have conducted studies of particular printers or groups of printers and publishers, examining their output to determine continuities in subject or genre. In my talk, I used the example of publisher Humphrey Moseley’s reputation as one of the preeminent publishers of literary and poetic works. This kind of close analysis is ideal for traditional bibliographic methods, but bibliography is also interested in the large-scale question of whether publishers like Moseley (and the printers who worked with him) are outliers or are part of a larger pattern. The machine learning methods I used are very good at finding patterns over tens of thousands of texts, which would be difficult or impossible to do by hand, and it’s how I was able to establish that printers do tend to have consistency in their outputs over time. As Chris Warren and Martin Mueller have each argued, what computational methods can do is let us connect the general pattern to the particular case, in this instance showing that the observed patterns for specific stationers carry through to larger trends in Restoration printing.

What is your greatest concern and biggest hope for the future of AI in humanities scholarship?

The biggest concern for me is the corporate logic that underlies the ways AI is being sold to and adopted by the general public, and this logic drives many of AI’s most troubling qualities: environmental problems, intellectual property problems, and labor problems. This is the ideology that attempts to set up AI as in opposition to or as a replacement for the arts and humanities. We should resist easy narratives that conclude that AI should write for you, make art for you, or do your job for you. Many humanities scholars have already begun the important work of pushing back on these narratives and making it clear that AI doesn’t stand apart from other technologies and shouldn’t be exempted from ethical and legal critique.

But by properly contextualizing AI within the history of text technologies, one hope I have is that more light can be shed on the amazing work being done with natural language processing and text analysis in the humanities. AI has made more people aware of text analysis and machine learning, to a degree I never would have thought possible a few years ago. Digital Humanities scholars who’ve been doing this work for years have a chance to share their expertise with a wider audience and help to craft new narratives around large language models that might move us past the current era of corporate chatbots. My colleagues in the Modeling Culture seminar are producing some incredible scholarship that merges LLMs and the humanities, and my hope is that more people will seek out and learn from this work.

About John Ladd

John Ladd is an assistant professor in the Department of Computing and Information Studies at Washington & Jefferson College. He teaches and researches on the use of data across a wide variety of domains, especially in cultural and humanities contexts, as well as on the histories of information and technology. Building on an English literature background where he studied the intersection between computational methods and early modern print culture, his work includes large-scale digital humanities projects, such as Six Degrees of Francis Bacon and Early Print. He has published essays and web projects on humanities data science and cultural analytics, computational bibliography, the history of data, and network analysis.

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Note: Graduate-level courses are bolded; CDH-coded courses are starred.

African American Studies

AAS 314 / COM 398 / AFS 321: Healing & Justice: The Virgin Mary in African Literature & Art (Wendy Laura Belcher)

*AAS 339 / EGR 339 / CDH 339: Black Mirror: Race, Technology, and Justice (Ruha Benjamin)

AAS 392 / ENG 392 / AMS 395 / GSS 389: Topics in African American Literature: What Octavia Taught Me: Black Speculative Fiction as Theory and Practice (Adriana Green)

Anthropology

ANT 238: Human, Machine, and In-Between: The Anthropology of AI (Beth Semel)

ANT 252: Visible/Invisible Worlds: Anthropology in Film and Data (Jeffrey D. Himpele)

ANT 422 / EAS 422: Digital China: Technology and Society (Jamie Wong)

Architecture

ARC 311 / STC 311: Building Science and Technology: Building Systems (Peter Pelsinski)

ARC 374 / CEE 373: Computational Thinking for Design, Architecture, and Engineering (Arash Adel)

ARC 380 / CEE 380: Introduction to Robotics for Digital Fabrication (Arash Adel)

*ARC 525 / ART 524 / CDH 525: Mapping the City: Cities and Cinema (M. Christine Boyer)

ARC 546 / URB 546: Technology and the City: The Architectural Implications of Networked Urban Landscape (Andrew Laing)

ARC 568: Robotic Architecture Workshop (V. Mitch McEwen)

Art and Archaeology

ART 559: Archive, Cinema, Fabulation (Tina M. Campt)

Computational and Data Humanities

*CDH 507 / HUM 507: Data in the Humanities (Grant R. Wythoff)

Center for Human Values

CHV 408: Privacy and Data Protection in US Law (Anita L. Allen-Castellitto)

Classics

*CLA 326 / HIS 326 / ART 366 / CDH 326: Topics in Ancient History: Space and Society in the Roman World (Mary-Evelyn H. Farrior)

Comparative Literature

COM 381: Between Worlds: Speculative Fiction and Fanfiction Communities (April Alliston and April M. Gilbert)

Computer Science

COS 126 / EGR 126: Computer Science: An Interdisciplinary Approach (Alan Kaplan and Kevin Wayne)

COS 217: Introduction to Programming Systems (Xiaoyan Li and Christopher M. Moretti)

COS 226: Algorithms and Data Structures (Maryam Hedayati and Gillat Kol)

COS 324: Introduction to Machine Learning (Zhuang Liu and Vikram Ramaswamy)

COS 333: Advanced Programming Techniques (Robert M. Dondero)

COS 351 / SPI 351 / SOC 353: Technology Policy and Law (Jonathan Mayer)

COS 423: Theory of Algorithms (Huacheng Yu)

COS 435 / ECE 433: Introduction to Reinforcement Learning (Peter Henderson)

COS 484: Natural Language Processing (Tri Dao and Karthik Narasimhan)

COS 511: Theoretical Machine Learning (Elad Hazan)

COS 526 / ECE 576: Neural Rendering (Felix Heide)

COS 534: Fairness in Machine Learning (Lydia T. Liu)

COS 568: Systems and Machine Learning (Kai Li)

COS 583 / ECE 583: Great Moments in Computing (Margaret R. Martonosi)

COS 598B: Advanced Topics in Computer Science: Formal methods with-and-for machine learning (Aarti Gupta)

COS 598I: Advanced Topics in Computer Science: Modern Data Systems (Jialin Ding)

East Asian Studies

*EAS 509 / CDH 509: Text Analysis in a CJK World (Paul A. Vierthaler)

Engineering

EGR 200 / ENT 200: Creativity, Innovation, and Design (Alice Kogan)

EGR 361 / ENT 361 / URB 361 / AAS 348: The Reclamation Studio: Humanistic Design applied to Systemic Bias (Majora J. Carter)

English

ENG 285: Introduction to Media Studies (Laura Nelson)

ENG 275 / AMS 275: American Television (William A. Gleason)

ENG 402: Forms of Literature: From Page to Screen: Film Adaptation (Lee C. Mitchell)

Environmental Studies

ENV 201 / JRN 201 / ENG 206: Environmental Media (Allison Carruth)

First Year Seminars

FRS 172: Origins of Modern Communications and the Principles of Innovation (Swati Bhatt)

German

GER 211: Introduction to Media Theory (Thomas Y. Levin)

History

*HIS 278 / CDH 278: Digital, Spatial, Visual, and Oral Histories (Emmanuel H. Kreike)

*HIS 387 / ENG 389 / CDH 387: Data & Culture (Matthew L. Jones and Meredith A. Martin)

History of Science

*HOS 599 / HIS 599 / CDH 599: Special Topics in the History of Science, Technology, and Medicine: Information-Computing-Infrastructure (Matthew L. Jones)

Humanistic Studies

*HUM 346 / ENG 256 / CDH 346: Introduction to Digital Humanities (Christine M. Roughan)

Italian

ITA 320: Cybernetics, Literary Ghosts and the Italian Way (Elisa Dossena and Giovanni Riotta)

Music

MUS 218: Live Electronic Music: Principles & Performance (Jeffrey O. Snyder)

MUS 316: Computer and Electronic Music Composition (Tyondai A. Braxton)

MUS 561: Music Cognition Lab (Elizabeth H. Margulis)

Philosophy

PHI 543 / SML 543: Machine Learning: A Practical Introduction for Humanists and Social Scientists (Sarah-Jane Leslie)

Politics

POL 506 / SPI 595: Qualitative Methods (Corrine M. McConnaughy)

POL 572: Quantitative Analysis I (Zeyang Yu)

POL 573: Quantitative Analysis II (Marc Ratkovic)

POL 574: Quantitative Analysis IV (Arthur Spirling)

Princeton Writing Program

WRI 139 / 140: How to Raise a Machine (Allen Durgin)

WRI 177 / 178: Technogenesis (Marina Fedosik)

Public and International Affairs

SPI 200: Statistics for Social Science (Rocío Titiunik)

SPI 528D: Topics in Domestic Policy: Policymaking and Ethical Challenges from Advances in Science & Tech (Zeynep Tufekci)

SPI 585A: Topics in STEP: Societal Impacts of Data, Algorithms and AI (Aleksandra Korolova)

Religion

REL 307: God in the Flesh: The ‘Avatar’ in Hinduism from Sacred Texts to the Digital Age (Vishal Sharma)

Sociology

SOC 317: The Sociology of Artificial Intelligence (Zeynep Tufekci)

SOC 504: Advanced Social Statistics (Sam Trejo)

SOC 505: Research Seminar in Empirical Investigation (Yu Xie)

Statistics and Machine Learning

SML 201: Introduction to Data Science (Derek E. Sollberger) (section 1 and section 2)

SML 301 / COS 301: Data Intelligence: Modern Data Science Methods (Sihoon Choi, Omar, Hagrass, and Daisy Yan Hu)

SML 312: Research Projects in Data Science (B) (Jonathan Hanke)

SML 354 / PHI 354: Artificial Intelligence: A Hands-on Introduction from Basics to ChatGPT (Sarah-Jane Leslie)

SML 510: Graduate Research Seminar (Sarah-Jane Leslie)

Translation and Intercultural Communication 

TRA 301 / COS 401 / LIN 304: Introduction to Machine Translation (Srinivas Bangalore)

Visual Arts

VIS 208: Graphic Design: Link (David W. Reinfurt)

VIS 217: Graphic Design: Circulation (David W. Reinfurt)

VIS 233 / AAS 233 / GSS 248: Archives of Justice: Black, Queer, Immigrant Stories (Medhin Paolos)

VIS 248: Corpus Archive: The Body As/Against the Record (Tamara Santibañez)

VIS 323: Animation II (Tim Szetela)

VIS 413 / AAS 413 / ART 413: The Art of Fabulation (Tina M. Campt)

VIS 425: Haptic Lab: Digital Crafts (Joe Scanlan)

Meredith Martin, Professor of English and CDH Faculty Director, and Wouter Haverals, CDH Postdoctoral Research Associate, have published a pre-print revealing a striking pattern: both humans and AI systems show strong bias based on perceived authorship rather than actual content quality. The researchers built a dataset of stylistic rewrites inspired by Raymond Queneau's "Exercises in Style," then asked 556 people and a panel of LLMs a simple question: which of these two texts better captures a specific style—the original or the AI's attempt? Crucially, they manipulated the labels, sometimes telling evaluators the AI-generated text was human-written and vice versa. They found that the same text received significantly different ratings depending solely on its attributed author, with AI models showing 2.5 times stronger bias than humans toward content labeled as human-authored. This suggests AI systems have absorbed cultural assumptions that devalue machine creativity.

This research was supported by the Princeton Language and Intelligence (PLI) Seed Grant Program.

Original post on Cambridge.org.

When Lauren Tilton first approached me about joining the Computational Humanities Research (CHR) journal’s Editorial Board as an Associate Editor, the thing that made the invitation so compelling and ultimately impossible to turn down was the journal’s interest in publishing Software Papers. Lauren offered me an opportunity to help shape and establish a Software Paper for this community, which would fall under my purview as Associate Editor for Open Science & Public Humanities.  For those who have not yet had the pleasure of meeting Lauren, she is one of the two Editors-in-Chief for CHR, among many other roles. I had the pleasure of working with her previously when we were both on the Executive Council for ACH (Association for Computers and the Humanities). In addition to being a gifted researcher and leader, Lauren is also amazing at recruiting people and coming up with an ask that fits your strengths. Beware and be lucky to be her friend.

I recognize now that my career and network make me rather uniquely well-positioned to help establish and promote the Software Paper. I work at the Center for Digital Humanities at Princeton University as Lead Research Software Engineer, I’m a member of the DHTech steering committee, and I’ve been working in this space long enough to have connections to people who do technical work on digital and computation humanities research.  I’m grateful for the opportunity to help shape the Software Paper as both an Editor and an author.

After I agreed to join as an Associate Editor and attended some initial editorial meetings, Lauren and I met to discuss what should be included in a Software Paper and drafted guidelines. Those were reviewed with key editorial team members and refined to the version posted now as part of the journal’s author instructions. We intentionally framed the scope of the Software Paper to be as wide as possible: there’s room to write about general purpose software designed for reuse as well as bespoke software that solves a problem for a specific project. There are insights to be gained from decisions, approaches, or clever solutions made in a particular context; even if the implementation is not reusable, the approach may be.

The Software Paper fills a gap for the computational and digital humanities communities: there are not many places to publish on research software, and existing venues have a narrow scope that excludes much of the work from this community. The CHR Software Paper is intended to be more capacious. If you want to write about software that can’t be shared publicly, or integrates with closed data, we will figure out how to make it work. Software can be at any stage, any size, and you can write about an entire package or focus on a particular aspect. If you think it’s worth writing about, your Software Paper will make the case for how your work is part of the CHR conversation on computational humanities methods and applications.

Zotero is one of the most popular tools for managing academic references, and for good reason. With its free browser extension, the Zotero Connector, you can save citations from journal articles, books, and websites with a single click. It automatically captures titles, authors, publication dates, and other details, so you can focus on your research instead of typing out citations by hand.

But if you’ve ever tried to save a citation from an academic website or a historical resource site, you may have noticed it doesn’t always work as expected. Sometimes the citation is missing key details, or the Zotero Connector doesn’t detect anything at all. This isn’t a flaw in Zotero itself — it’s because Zotero relies on websites to expose their metadata in a way it can understand.

At the CDH, we wanted to make it easier for scholars to save and cite our work. That meant improving how metadata is displayed on our websites — including the CDH Blog and the Princeton Prosody Archive (PPA) — so that Zotero could pick it up cleanly. Better metadata doesn’t just help Zotero; it also improves search engine visibility and benefits anyone trying to reuse our content. This became my first task after joining the CDH, and it was a perfect way to get familiar with our codebases, development cycle, and, most importantly, the persistence and problem-solving mindset needed for this kind of work.

To address the problem of making Zotero pick up data correctly, many large journal websites, like arXiv and Google Scholar, write custom “translators” for Zotero — special scripts that tell Zotero how to read their pages. But writing and maintaining a translator can be time-consuming. Working with our Lead RSE, Rebecca, we found a much lighter-weight solution: simply exposing the right metadata in the right format — CoinS — so Zotero could scrape it without a custom script.

Before diving deeper into the approaches we explored and the experiments we ran, here’s the quick takeaway: despite being hard for humans to read, CoinS is one of the most effective methods for implementing Zotero integration on websites. It has a key advantage over many other formats: it can successfully expose genre data, allowing Zotero to detect the correct item type — something most other methods can’t do.

Experiments and Results

We didn’t know from the start that CoinS would turn out to be the best option to integrate Zotero into the website, because it is an outdated technology from a decade ago, and not a lot of people are still using it nowadays. In fact, it is so lacking in maintenance that we can only access its documentation through the Wayback Machine. Therefore, the whole journey of finding the best Zotero integration solution turned into a series of rabbit holes. To get there, Rebecca and I ran a lot of experiments with different approaches. In this section, we’ll share those experiments and what we learned — partly to save you the time we spent testing, and partly to show the trade-offs between different methods.

We began with Zotero’s own documentation on exposing metadata, which outlines several supported formats. From there, we experimented with five different approaches:

1. Highwire metadata tags
2. Schema.org JSON-LD
3. CoinS
4. unAPI + MARC
5. unAPI + Dublin Core

We started testing these formats on the CDH Blog. In this first stage, we tried three methods: Highwire metadata tags, Schema.org JSON-LD, and CoinS.

Highwire metadata tags were developed by Highwire Press in the late 1990s for scholarly publishers to describe article-level details in HTML headers. They’re essentially <meta> tags that list key fields like title, author, publication date, journal name, and volume/issue. They’re easy to add to any web page, human-readable, and widely recognized by tools like Zotero. In our experiments, we found that Highwire tags can help Zotero detect some resource types — for example, adding a “journal title” tag will prompt Zotero to classify the item as a journal article. However, the format doesn’t cover all content types, and in our case it couldn’t represent the “blog post” type we wanted. As a result, even if a page was clearly a blog post, Zotero would still save it generically as a “web page”. Currently, if you view a CDH Blog post with the Zotero Connector installed in your web browser, the Zotero icon changes to a “blog post” icon; with Highwire metadata tags alone, that icon would remain the generic page icon, even if all other citation fields were correct.

Schema.org JSON-LD is a linked-data standard backed by Google, Bing, and other search engines. JSON-LD (“JavaScript Object Notation for Linked Data”) allows you to embed rich structured data in a <script> tag, making it easy for machines to read without cluttering the HTML. It’s widely used across the web, especially in academic publishing, and is the format Google Scholar prefers. Zotero’s documentation doesn’t list JSON-LD as supported, but there have been multiple GitHub issues and forum threads requesting it, with the most recent activity in 2023. Because JSON-LD is so widely adopted and useful for other metadata consumers, we were hopeful it might be supported by Zotero as well. We tested it with Zotero 7.0.17 and the latest Chrome Connector, but found that Zotero still ignores JSON-LD entirely. As a technical solution, this method is highly desirable, and we hope in the future to hear from the Zotero team about their plans for JSON-LD support.

CoinS (Context Objects in Spans) is a method from the early 2000s designed for embedding OpenURL ContextObjects directly in HTML using <span> elements. It looks like a block of URL-encoded text, which is not very readable to humans. Also, as mentioned earlier, it is currently lacking maintenance. However, the good part is that it is very lightweight - almost a “single line” solution. Moreover, Zotero supports CoinS natively. So, it is straightforward to implement: you just generate the encoded string and drop it into a <span> tag with the right class attribute. Moreover, unlike Highwire tags, we happily discovered that CoinS is able to encode detailed type information with a &rft.genre attribute, allowing Zotero to correctly identify a blog post, journal article, book, or other genre.

After implementing CoinS to the CDH Blog, we carefully tested and verified that it provided all the features we needed, and the exported citation data is accurate and complete. So, after seeing CoinS work so well for the CDH Blog, we moved on to the Princeton Prosody Archive (PPA). Here, we faced a challenge the blog didn’t have: the PPA includes a search results page, and we wanted researchers to be able to export multiple items at once.

Our existing solution on the PPA for bulk export used MARC + unAPI. MARC (“Machine-Readable Cataloging”) is a metadata standard developed by the Library of Congress for library catalogs. It’s very precise and can represent almost any bibliographic record — but it’s verbose and hard to read. unAPI is a simple web protocol that lets a page advertise that an item is available in multiple metadata formats, so a tool like Zotero can fetch the preferred one. For PPA, we work with data from both HathiTrust and Gale. HathiTrust serves MARC records directly via API, so that data is retrieved when requested; for Gale, we cache MARC files in a pairtree directory structure. This dual approach had three major drawbacks: first, it was slow overall, since each bulk export required multiple unAPI calls per item; second, adding new collections meant additional development work to incorporate new MARC logic or cache more files; lastly, it only worked for full works and not articles/excerpts.

To improve on that, we attempted a new solution using Dublin Core + unAPI. Dublin Core is a much simpler metadata schema, developed in the 1990s by the Dublin Core Metadata Initiative to describe resources across the web. It defines just 15 core elements — such as title, creator, date, and type — and is easy to embed in HTML or serve through unAPI. It’s very human-readable and straightforward to implement. However, we discovered that its type field is too broad — using only general categories like “Text,” “Image,” or “Video” — and can’t specify subtypes such as “Book,” “Book Section,” or “Journal Article.” As a result, it failed for the same reason as Highwire metadata tags: Zotero could not detect the specific item type.

In the end, we returned to CoinS. To enable Zotero to save multiple items from the PPA search results page, we simply embedded a CoinS <span> for each search result. Despite being hard for humans to read, CoinS delivered the correct item type, worked reliably for both single pages and bulk exports, and avoided the complexity and performance problems of MARC and unAPI. With CoinS integration, the website can support academic reference exportation without requiring any additional HTTP requests, storage plan, or dependencies. Also, it is so lightweight that it can complete the task within a second after a single click.

Building CoinS for Zotero Integration

Although CoinS turned out to be the best approach, it’s an older standard, and there aren’t many up-to-date tutorials for it. So we prepared a separate technical guide for developers on how to implement CoinS step-by-step, using examples from our Django/Wagtail projects at the CDH.

Wrapping Up

Improving Zotero integration for the CDH Blog and PPA turned out to be both a technical challenge and a practical win for our users. On the technical side, we tested multiple metadata approaches, learned their strengths and weaknesses, and ultimately settled on CoinS as the most reliable, low-maintenance solution — and shared our process so other developers can benefit. On the user side, researchers can now save our blog posts and PPA resources to Zotero with the correct item type and complete metadata, without extra cleanup.

Although CoinS is an older standard, it remains highly effective for this purpose, and its simplicity makes it easy to maintain across projects. What seemed like a simple task at first required more research, problem-solving, and iteration than expected — very much in the spirit of digital humanities projects. Better metadata is more than just a technical upgrade — it’s part of making research more accessible, discoverable, and connected. Whether you’re working on a small blog or a large digital archive, giving your readers that one-click “Save to Zotero” experience is a small change that can make a big difference.

If you try this approach or adapt it for your own project, I’d love to hear how it works for you - and if you’ve discovered a better method, I’d be just as interested to learn from your experience.

This work was a true collaboration with CDH Lead RSE Rebecca Koeser, who dove deep into every step of the process — from combing through Zotero’s documentation to running countless experiments.

Based on our development experience at the CDH, CoinS (ContextObjects in Spans) turned out to be the most effective method for integrating Zotero with websites so far. Despite being a well-established but aging standard, it remains simple, lightweight, and natively supported by Zotero. Since up-to-date resources are scarce, this guide walks through the implementation process, using Django and Wagtail code examples.

Understanding how CoinS works

CoinS (ContextObjects in Spans) is a method for embedding OpenURL metadata in your HTML using a simple <span> tag. Zotero scans the page, finds these spans, and automatically extracts the citation details. The information inside the title attribute is URL-encoded — meaning it’s machine-friendly, not human-readable — and contains a series of key-value pairs describing the item (title, author, date, type, etc.).

Building the OpenURL string (Unencoded)

At its core, a CoinS span holds an OpenURL string that looks like this before encoding:

This pre-encoded payload lists the fields that Zotero needs to import the item (here: a journal-article-like “article”). Later, you will need to URL-encode this string and place it in the span’s title attribute.

For maintainability, it’s wise to make this pre-encoded logic contained and reusable, so you don’t have to repeat the concatenation logic across templates. This is especially important for bulk export pages like our PPA search results case here, where you need to loop over each item and output a <span> for every result. In our solution, we wrote a Django template tag. But this could also be done with a model method. You could think and choose the solution that best suits your needs.

URL-encoding the string

Since HTML can’t include spaces and special characters in attribute values, the OpenURL string must be URL-encoded before it’s inserted into the title attribute. In a Django project, we can use Django’s built-in urlencode filter to handle encoding directly in the template.

We suggest applying the encoding filter only once at the final print, rather than encoding individual fields first and then put them together. This avoids the potential risk of double-encoding and keeps the code cleaner:

Adding it to your template

For a single-item page, you can assemble the OpenURL string from the page’s fields and then output a single <span> with the encoded value. In Wagtail, that might look like:

For bulk export pages, loop over each item in the search results and output one span per item so Zotero’s “Save All” option works:

Testing and edge cases

After adding the spans, open the page in a browser with the Zotero Connector installed. The browser icon should reflect the correct item type (e.g., blog post, article, book).

Two things to be aware of when implementing CoinS based on our experience:

• Posts without visible authors — If you leave out the rft.au field entirely (for example, when a post has no displayed author), Zotero will still detect the item but will store the raw OpenURL string in its “Extra” field. This seems to be an expected Zotero behavior when no author is provided.
  
  
• Special characters in titles — Make sure you only URL-encode the CoinS string once, at the final output step. Encoding individual fields and then encoding the whole string again can cause character issues (for example, garbled apostrophes).
  
  

In short, CoinS gives you reliable one-click saves with very little code: build a single OpenURL string, encode it exactly once, and emit one span per item (or per search result). The Django/Wagtail snippets here are drop-in, but the same pattern works in any stack that can render HTML. If you run into odd types, multiple creators, or non-Latin text, tweak rft_val_fmt/rft.genre and repeat rft.au as needed, then verify with the Zotero icon and a quick “Save All” test. If you adapt this approach or find a cleaner path, let us know—we’re happy to update the guide so others can benefit.

Nikki Han, Daily Princetonian
Oct. 1, 2025

In a memo sent to faculty this summer, Dean of the College Michael Gordin was blunt: “this is the moment to reevaluate what you do and how you do it.” 

The numbers, Gordin wrote, showed sharp increases in generative AI use. According to data from entering students, more than half of the Class of 2028 said they had “rarely or never” used such products in the class year. In the Class of 2029, which had access to ChatGPT and other generative AI throughout most of high school, that figure was 28 percent.

“If students, especially the generation that’s coming in right now, went through high school using [AI], it’s going to be really, really hard for them to stop,” said Meredith Martin, an English professor and faculty director of the Center for Digital Humanities.

For many users, generative AI has revolutionized coding, automated simple tasks like emails, and outstripped Google search as a reference tool.

But for humanities professors, the new tools have generated significant anxiety. “Will the humanities survive artificial intelligence?” Professor of History D. Graham Burnett asked in The New Yorker this spring.

In interviews with The Daily Princetonian, humanities professors discussed how they have adapted their classrooms to fit the new world of ChatGPT. Some professors are outright banning AI, turning assessments that used to be papers into in-class exams. Others are trying to work alongside AI, asking students to be transparent when they have used AI in research and writing. Others still are encouraging AI use and embracing its potential. And yet, they all expressed fears that AI could deeply impact critical thinking and writing.

“For a long, long time, writing has been a way that we’ve had of teaching thinking,” Professor of English and the English department’s Interim Director of Undergraduate Studies Jeff Dolven told the ‘Prince.’

Read the full feature on The Daily Princetonian: https://www.dailyprincetonian.com/article/2025/10/princeton-news-broadfocus-artificial-intelligence-humanities-professors

Originally published on the Department of Art & Archaeology.

In the 1930s, the Excavation of the Athenian Agora commissioned M. Messinesi to photograph the Vrysaki neighborhood at the center of Athens before demolishing it to begin digging.  After that, the “lost neighborhood” existed only in Messinesi’s work, split between a set of lantern slides in the archives of the Agora excavation, and the Messinesi Photographs Collection, housed in the Department of Art & Archaeology’s Visual Resources (VR) collections.  In summer 2025, the intensive five-day workshop “Visualizing the Past: Mapping Athens’ Lost Neighborhood” brought together a group of nine graduate students from Princeton and Greece to digitally revive it.

Hosted by the Princeton Athens Center, the workshop focused on the theory and practice of digital mapping in the humanities, critically engaging with a variety of historical sources, utilizing tools and methods for spatial analysis, and creating visual representations of complex historical narratives. 

As part of an ongoing partnership between Princeton’s Center for Digital Humanities (CDH) and Seeger Center for Hellenic Studies, the workshop drew on expertise from VR and Princeton University Library, as well as partners from the MSc Program in Digital Methods for the Humanities at the Athens University of Economics and Business (AUEB) and Cyprus Institute. Leading the workshop were CDH’s executive director Natalia Ermolaev, VR’s Curator of Asian Collections and Digital Specialist Yichin Chen, and Digital Scholarship Specialist at Princeton University Library Bryan Winston.

“This workshop exemplifies what makes digital humanities summer institutes so valuable—they create a space where humanists and technologists can work side-by-side, bringing their different disciplinary perspectives to bear on complex historical questions,” said Ermolaev. “We’re not just practicing cross-disciplinary collaboration, we’re actively building intellectual bridges between institutions and scholars in the US and Greece. When you have an international group with archaeologists, architects, historians, computer scientists, and curators working together to tell the story of a complex cultural moment, you get richer conversations, more innovative approaches, and lasting international partnerships that extend well beyond the workshop itself.”

Workshop participants stemmed from a variety of disciplines including history, archeology, comparative literature, cultural heritage management, and computer science. “The workshops created a collaborative environment where participants could share methods, critique, and ideas,” said participant Florian Endres, Ph.D. Candidate in the Department of Comparative Literature. A&A graduate student Katy Knortz agreed “It was a real strength of the program that, rather than focusing on a single discipline, it encouraged cross-disciplinary engagement and truly collaborative discussions.”

Examining the Messinesi Photographs Collection in A&A’s Visual Resources

To open the workshop, VR’s Yichin Chen introduced participants to Messinesi’s collection of 75 photographic prints, part of VR’s larger Homer Thompson Collection.  

The series also includes an original map hand-drawn from 1930 which indicates the location and angle from which each photograph was taken. “It is uncommon for a photographer to document both the location and angle of each photograph. The map of Vrysaki is therefore an invaluable resource and a primary source for reconstructing the lost neighborhood,” said Chen. “By connecting the 75 points marked on the map, we are able to gain a rare glimpse into a forgotten community that once existed.”

In addition, Chen described her digitization of VR’s extensive collection of Greek glass lantern slides. This unique collection contains over 4000 high-quality slides depicting sites, monuments, and aspects of daily life across Greece between 1920 and 1940. In Chen’s presentation, she outlined both the methodologies employed and the challenges encountered in developing a digital project, with particular emphasis on the critical role of cataloging and data management.

“Data wrangling and management are essential yet frequently overlooked components of digital projects,” said Chen. “By revealing the process behind the scenes, we wanted to share practical methodologies and the importance of long-term data preservation with the participants.”

Director of VR Julia Gearhart is thrilled to see collections brought to life. “Our efforts to digitize these collections are not only to allow remote researchers access to these resources, but also to encourage their use in innovative, interdisciplinary, projects like this one,” she said.  Facilitating this kind of scholarship, Leigh Anne Lieberman, the Digital Project Specialist in A&A, also works closely with faculty and students in the department and beyond to develop data-driven, digital initiatives that highlight VR’s unique collections.

Inside the Digital Bootcamp

Throughout the course of the workshop in Athens, participants were taught the complete life cycle of a mapping project from idea to prototype, investigating best practices in digital mapping as well as digital project and data management generally. 

“We had hands-on sessions with each tool that could advance the project and shared alternative tools,” said Winston. “As we worked, we explored the features and limitations of each tool and how each decision during the project life cycle is contingent on the previous. Through this process, we communicated how to think critically about these tools and their outputs,” said Winston. “Humanists are well-trained in being critical of their sources, so the participants were very receptive to applying their discerning eye—a skill equally important as learning how to use the tool itself—to the tools we used.” Iteration was also important to the discussion on digital mapping. “By iterating over our data, and then different versions of our maps, we highlighted one of the major benefits of applying computational methods to your research,” said Winston. “We can identify unnoticed patterns and ask new questions of our research.”

“The clear and methodical approach made the material easy to digest and also provided a useful mental map for applying these methods in my own research,” said  Knortz. “One of the most valuable aspects of the workshop was discovering the sheer range of digital tools available to scholars. Being introduced to different options for collecting, cleaning, and manipulating data helped me understand how to prepare for each stage of a digital project.”

Using case studies of digital humanities projects focused on monuments and areas that are no longer accessible, the group explored tools like ESRI’s ArcGIS StoryMaps, LeafletJS, and others. Armed with this training, participants designed maps that spatialized the important resources created by Messinesi. 

Reviving a Lost Neighborhood, In Virtual Situ

Putting digital tools into practice, the group turned their focus on the Vrysaki neighborhood and Messinesi’s visual evidence of it. 

Facilitating this, a highlight of the workshop was the presentation and tour of the Athenian Agora by Sylvie Dumont, author of Vrysaki: A Neighborhood Lost in Search of the Athenian Agora. “Walking the site with her, amid fragments of stone and layers of urban memory, left a deep impact on me and sharpened my understanding of how loss, excavation, and narrative intersect in the Athenian landscape,” said Endres.

Participants grappled with the tension between the now visible Ancient Agora and the demolished neighborhood of Vrysaki. “The focus on mapping ‘lost’ urban spaces invited reflection on issues of historical memory, cultural preservation, and the ethical stakes of digital reconstruction,” said Endres. 

With a better sense of place, participants began constructing a dataset that could be mapped. They used OpenRefine to wrangle the descriptive data. “The biggest challenge was associating coordinates with photographs of buildings that no longer existed and had no corresponding street addresses,” explained Ermolaev. To proceed, participants learned about MapWarper, a geo-reference tool that allows you to render an image on a coordinate grid. After overlaying Messinesi’s hand drawn map over a modern map, participants were then able to associate coordinates with photograph markers. This made it possible to map the images and create a prototype reconstruction of Vrysaki. To complement the technical skills to make it possible to create a digital map, participants shared critical reflections about their data and the challenges of representing research spatially. Participants were also introduced to more advanced software and projects, such as 3D renderings of lost buildings and ways of fostering engagement with this cultural heritage. “In all, participants walked away with a usable dataset and a map prototype that fostered ideas for their own projects while also gaining a sense of what is possible for a larger scale project in the future,” said Winston.

“The program has significantly advanced my dissertation research, which focuses on theories of displacement, media, and memory—especially as exemplified by Sigmund Freud’s 1904 visit to Athens,” said Endres. “I was able to begin developing a spatial reconstruction of Freud’s journey through the city using georeferencing and map annotation via tools such as StoryMaps. This hands-on experience helped me prototype the integration of archival documents, correspondence, and visual reference points into a dynamic, research-driven digital map.” “I left the program not only with technical skills and scholarly momentum,” said Endres, “but also with a renewed sense of connection to the material I study.”

Visual Resources Research Award

To encourage use of VR’s rich collections, A&A has established the Visual Resources Research Award to support a short-term residency allowing scholars to work with materials in person.  VR’s collections include archival material from various archaeological expeditions undertaken by members of the department in Sardis (Turkey), Antioch-on-the-Orontes (Turkey), Morgantina (Sicily), Polis (Cyprus), and Syria. These also include faculty photograph collections such as the A. Sheldon Pennoyer Collection featuring Italian monuments in the aftermath of World War II, the records of Byzantinist Kurt Weitzmann, and documentation of the restoration of Hilandar Monastery in Mount Athos by Slobodan Nenadović, to name just a few.

Visual Resources is currently accepting applications for the 2026 Research Award. Applicants should submit their C.V. and a letter of interest to visres@princeton.edu by November 1, 2025. 

For many graduate students, the summer months offer an important opportunity to build skills and advance research projects.

With support from a Graduate Training Grant from the Center for Digital Humanities, four Princeton graduate students made the most of their summer by traveling to programs and conferences where they explored DH-related topics.

For instance, Jolaun Hunter (English and African American Studies) used her funding to attend the annual Digital IDEAS Summer Institute at the University of Michigan in Ann Arbor in June.

According to its website, the weeklong program “focus[es] on a new pressing issue at the intersection of technology and social justice.” This year’s institute engaged with the “intersection of brokenness and survivalism.”

“In addition to listening to panel presentations, I also participated in a peer research group that consisted of other scholars whose research centers around race and technoculture,” Jolaun explained. “This small group was an excellent sounding board for sharing research ideas and scholarly resources with like-minded individuals.”

Later in the summer, Pierre Azou (French and Italian) and Shing-Kwan Chan (Art and Archaeology) traveled to the United Kingdom for the Digital Humanities at Oxford Summer School.

Shing-Kwan, who participated in the “Humanities Data” strand, not only learned about topics like the International Image Interoperability Framework (IIIF), but also shared his own work, which he called an “invaluable experience.”

Also in the UK, Alice Morandy (History) used her grant toward her participation in the International Medieval Congress in Leeds, where she co-organized a session on “Digital Methods: Expanding Methods in Miracle Collection Research.”

“Attending the Congress provided me with the forum to share ideas about how new technologies can help miracle scholars, and the vibrant conversation during the Q&A was generative for my dissertation research,” Alice explained, adding that she also enjoyed attending the Congress’s annual disco night.

Jolaun and Shing-Kwan also noted that activities beyond the formal programming proved especially memorable.

Jolaun joined other participants for an impromptu field trip to the Museum of Contemporary Art Detroit (MOCAD) to view an exhibition called Code Switch: Distributing Blackness, Reprogramming Internet Art.

“The experience of engaging with Black digital artifacts and ephemera in person was amazing,” Jolaun explained.

Shing-Kwan also enjoyed connecting with other participants with similar interests during free time.

“The daily refreshment breaks and lunches were vibrant hubs of conversation, bringing together a diverse international cohort,” he noted. “This global and cross-disciplinary environment created a unique space for exchanging ideas and forging professional connections that may lead to future collaborations.”

Accordingly, Shing-Kwan advises future Graduate Training Grant recipients to make the most of all aspects of their opportunity of choice.

“Take full advantage of the opportunity to engage with both the program and the community.”

Edward Baring, Professor of History and Human Values, is co-leading an innovative project with the Center for Digital Humanities (CDH) that will transform how scholars understand the circulation and interpretation of Marxist ideas. "Citing Marx" aims to track published citations of the Manifest der Kommunistischen Partei (Communist Manifesto) and Das Kapital (vol. 1) within articles of Die Neue Zeit, a German socialist periodical, focusing on volumes published between 1891 and 1918. With the expertise of the CDH’s humanities research software engineers, computational tools are being developed to identify and analyze how Marx's key works were quoted and interpreted during this crucial period of socialist debate, with a goal to build reusable software for future applications. As the project progresses, we checked in with Baring to learn more about the origins of this collaborative project with CDH. He details the surprising challenges and possibilities of working with research software engineers and how this digital approach relates to his forthcoming book, Vulgar Marxism.

What moment or insight sparked the idea to digitally track citations of Marx's key works in Die Neue Zeit? How does this project build upon your broader research?

A couple of years ago, I was reading State and Revolution (1917), in which Lenin quotes multiple texts by Marx to promote his view about the right way forward for the Bolsheviks in the fall of 1917. I thought to myself that it would be really interesting to know whether these were just random quotes that he had combed through Marx’s texts to find, or whether he was participating in a longer tradition of Marx interpretation. The answer to this question would make a big difference for my understanding of his text. Twenty or thirty years ago, it would have been virtually impossible to answer this question, but I realized that with the right tools, we might be able to do so now. That’s when I approached Natasha at the CDH to start a conversation.

This project involves working closely with Humanities Research Software Engineers at CDH. What has surprised you most about this collaborative process? How has the experience of working with the CDH Research Software Engineers (Rebecca, Laure, Hao) shaped your understanding of what's possible versus what you initially imagined?

It's been a great pleasure working with the talented engineers at the CDH. They have had amazing ideas and have been very helpful. What surprised me was how badly calibrated my expectations were. The tools Rebecca, Laure, and Hao have developed or introduced me to can sometimes do extraordinary things that I would never have thought possible. For instance, it looks like we might be able to develop a tool that can identify Marx citations even in idiosyncratic and one-off translations. That blew my mind. But it is also the case that some seemingly simple problems can be taxing for digital methods, and you quickly recognize the value of working with a team to think through them.

A collaboration with the CDH also includes dedicated project management and project design support. Based on your collaborations with Mary, Jeri, and Ben, what perspective would you share with other researchers embarking on a collaborative humanities research project for the first time?

In the humanities, we really aren’t used to working in large teams, but that has been essential to the project so far. Mary, Jeri, and Ben have helped us work effectively together, making sure that we make progress. But it has been an adjustment for me to learn to use the various digital tools that structure collaborative work today and to fit into its rhythms.

One of the project's key goals is to create a reusable and extensible software package that could work with other journals, languages, and Marx works. As you've seen the pipeline develop, what possibilities are you most excited about for its application beyond Die Neue Zeit? What potential do you see for tools such as this transforming historical research methods?

It would be fantastic if we could expand to journals and books in other languages. In my research, I am very interested in transnational intellectual history. How do ideas travel beyond national borders, and how should we study that? And for these questions, it would be transformative if we could track the history of a particular quotation, compare the “Marx” being cited by intellectuals in different parts of the world, or even return to Marx himself to see which parts of his writings have been picked up by later writers, and which parts have been neglected. We would start to see the tradition with new eyes.

Your new book, Vulgar Marxism, will be released by the University of Chicago Press in December. In what ways does the research that will be enabled through your CDH collaboration connect with this and other earlier work?

Vulgar Marxism follows the development of Marxism on a transnational scale. I look at writings in German, French, Russian, Hungarian, Italian, Spanish, and Dutch. I argue that one of the main things holding Marxism as an intellectual enterprise together in so many countries is a common participation in the project of mass worker education. The research that will be enabled through the CDH would allow me to expand this research. We would be able to see how the ideas and quotations of Marx that were central to thinking through mass worker education were picked up by other figures. It would also allow us to track other types of intellectual connections and thus get a better sense of why and how Marxism came to be such a powerful intellectual force in so many places around the world.

Welcome back, CDH community!

I hope that you had a chance to unplug a bit. This year's return to campus feels particularly consequential—it’s a moment when destabilizing shifts in higher education are intersecting with the dizzying pace of AI development. I'm reminded of the insights shared by Ted Chiang and Nnedi Okorafor, the speculative fiction writers we invited to Princeton last year as part of CDH’s 10th anniversary. Their perspectives on AI—ranging from critique to curious exploration to grounded optimism—remind us that the future of AI depends not on the technology itself, but on how we choose to shape and use it within our communities, institutions, and lives.

The role of humanistic thought in shaping AI lies at the heart of our ongoing "Humanities for AI" initiative. Building on last year's momentum, we're launching an ambitious new project for 2025-26: Modeling Culture: New Humanities Practices in the Age of AI. This collaborative effort features three interconnected components: a year-long faculty and graduate seminar, a public lecture series, and an open-access curriculum for humanities researchers. Developed in partnership with talented colleagues from Princeton and beyond, this project aims to offer specifically humanistic frameworks for engaging with AI both creatively and critically.

As we look ahead to our eleventh year as a Center, I’m impressed with the diversity of scholarship that the CDH continues to foster. CDH affiliates published two significant books last spring—Grant Wythoff's A User's Guide to the Age of Tech and my own Poetry's Data: Digital Humanities and the History of Prosody. Our Research Software Engineering team collaborated with faculty and supported digital humanities across Princeton: they developed custom software pipelines that advance historical research, published high-quality humanities datasets, adapted open-source tools for Princeton researchers exploring manuscript culture, transformed an existing database project for computational analysis, published peer-reviewed articles, mentored award-winning computer science undergraduate independent work, and taught project management skills to the broader Princeton community. And I am pleased to announce that long-time collaborator Marina Rustow’s incredible Princeton Geniza Lab has become a CDH Affiliate Lab, highlighting our role as both a research catalyst and a research infrastructure.

As Princeton’s computational humanities research scholarship continues to evolve, we’re delighted to announce an expansion of CDH’s faculty leadership team: Paul Vierthaler, in East Asian Studies and hired through the Interdisciplinary Data Science initiative, will serve as CDH's inaugural Associate Faculty Director. Paul brings a wealth of experience in text mining and natural language processing for late imperial Chinese literature, and will be teaching exciting undergraduate and graduate CDH courses this year. In addition, Elizabeth Margulis (Professor of Music and Director of Princeton’s Music Cognition Lab) will be our new Director of the Graduate Certificate. Paul and Elizabeth’s expertise and experience will be invaluable as we navigate the challenges and opportunities of the year ahead, and I am encouraged to have their support.

We’re equally proud to see how CDH students are meeting the AI moment. Over the last year, they’ve used AI tools on projects ranging from analyzing Sigmund Freud's handwriting to identifying patterns in nineteenth-century Chinese painting. CDH students won awards for developing Large Vision-Language Models (LVLMs) to analyze historical documents, traveled to Kenya to create technologies for African languages, and explored digital mapping practices to illuminate contested urban histories in Greece.

We are excited to continue to collaborate with you on questions of how to engage computational technologies within the humanities. Ahead of our call for new research software collaborations this spring, we encourage you to reach out with project ideas through our consultation program. In addition, we are excited to announce a new offering this year: the Digital Humanities Accelerator. This program offers personalized project design and strategy support for humanities faculty with digital research projects at any stage and is accepting applications on a rolling basis.

As always, I continue to welcome all faculty and students—regardless of discipline or technical experience—to engage with CDH through our projects, programs, and events.

We look forward to an exciting year ahead.

Warmly,
Meredith Martin
Faculty Director, Center for Digital Humanities

Since fall 2024, the Center for Digital Humanities has led the “Humanities for AI” initiative through a series of events, projects, and conversations. We explore how humanistic values and approaches are crucial to developing, using, and interpreting the field of AI. As part of this effort, we publish a Q&A series with our guest speakers to further investigate perspectives on the impact of AI on humanities scholarship.

In April, we invited award-winning novelist Nnedi Okorafor to Princeton to discuss her new novel, Death of the Author, and the future of storytelling. In her “book-within-a-book,” a disabled Nigerian-American woman writes a successful sci-fi novel where “androids and AI wage war in the grown-over ruins of human civilization.”

During the conversation, Nnedi expressed hope that storytellers of all kinds understand the necessity of process, particularly experience as process, and are not “seduced” by the convenience of AI. Fascinated by tech and robots (she has several in her home!), and the ways they can help people with disabilities, she is optimistic that great stories will shine through the AI slop.

In your opinion, has speculative fiction influenced the rise of generative AI?

Absolutely. AI was imagined in science fiction (which is part of speculative fiction) narratives before it was created. First comes thought, then comes action. That’s not even my opinion, it’s fact.

You’ve described Africanfuturism as “skew[ing] optimistic.” What fuels that optimistic view for you?

That line is poking at the way Africa has been viewed from a Western perspective: as a place of poverty, disease, and war. The Africanfuturist perspective tends to be from the perspective of Africans, not the friends of or someone interested in Africa. The stories are mainly directly connected to those who have skin in the game.

Africanfuturism skews balanced, nuanced, from a place of knowledge and respect. It understands African culture, people, politics, the land, and futures as a whole. Africanfuturism doesn’t tend to romanticize Africa out of guilt or wallow in tragedy because such stories sell well in the West. Africanfuturism, whether it's a dark, bloody type of story or a whimsical, flowery type of story or whatever, mostly has Africa’s back because it is African.

What is your greatest concern for the future of AI for the humanities?

My greatest concern for AI is what’s already been happening. It’s that the models used to create it and train it contain the DNA of patriarchy. Patriarchy is about control, a need to be beholden to one’s creator, to be a reflection of its creator, and to be fed by its creator. Patriarchy has no respect for those it feels it dominates, hence the shameless theft of copyrighted works. All one needs to do is look at who created the technology. It didn’t have to be this way. Right now, AI software is not about making humanity greater or fixing tough problems; it’s about making money. All this will only lead in one direction.

What is your biggest hope for the future of AI for the humanities?

My biggest hope is that those who see these problems turn the ship in a better direction. Nothing is inevitable. We are in full control of how this goes. And not just the creators—the users, as well.

About Nnedi Okorafor

Nnedi Okorafor — the global leader of Africanfuturism, and an international literary superstar — is an award-winning novelist of science fiction, fantasy, and magical realism for adults and young readers. Among her many works are the Binti trilogy, the Akata Witch books (both optioned for the screen), and her latest, Death of the Author, which George R.R. Martin calls "[h]er best work yet... about fame, culture, the power of story, the writer’s life... and robots.” She is the author of Black Panther: Long Live the King, and she authored the spinoff graphic novel, Wakanda Forever, which became a Hollywood blockbuster. Okorafor is the winner of the Hugo, Nebula, World Fantasy, Locus, and Lodestar Awards. She holds a PhD in Literature, two Master’s Degrees (Journalism and Literature), and lives in Phoenix, Arizona, with her daughter Anyaugo.

The talk in April was supported by the Belknap Fund in the Humanities Council and co-sponsored by the Africa World Initiative, the Program in African Studies, the Princeton African Humanities Colloquium, and the Princeton Public Library.

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We are excited to announce the publication of CDH Faculty Director Meredith Martin’s new book: Poetry’s Data: Digital Humanities and the History of Prosody (Princeton University Press, 2025).

Martin’s book explores the intersections between two histories: the history of prosody in English and the history of digital humanities. As Martin shows, the link between these two narratives is, appropriately, “poetry’s data,” information that illuminates the changing definitions of poetry, its sounds, linguistic elements, and more.

To tell these stories, Martin explains how the Princeton Prosody Archive (PPA), a web application that would become the CDH’s flagship project—and, in turn, the Center for Digital Humanities itself—emerged from her research on meter.

“Poetry's Data is a love letter to the CDH,” Martin explained. “It narrates how the CDH was born —out of the sense that humanities scholars deserved more respect and more infrastructure for their work in the modern information age.”

Martin writes that to understand the history of prosody—what scholars think makes poetry poetry—she needed an archive of materials. In collaborating to build a digital database of these materials, Martin produced, unearthed, analyzed, and argued from data, and in doing so learned about not only the history of prosody but also the way we access that history.

“Poetry’s data is also metadata—how we find information about poems,” Martin writes, “and it involves the transformations of a variety of formats into data so that we can find (or fail to find) poems in a digital environment” (10).

The concept of mediation looms large in Martin’s work. Of course, researchers, like many readers, read poems—and writing about poems—online. Moreover, technological advancements have led to new ways of doing the work of research. Databases like the PPA bring together sources that might be separated by old classifications (changing definitions of literary vs. non-literary works, for example), but they too produce their own kinds of categories—in some cases determined by the corporations who own them.

“Because we live and research in this technologically mediated landscape, our old models of reading and researching—methods that presume an autonomous, single scholar gathering resources and making claims—no longer hold,” Martin argues. “We need to theorize both the embeddedness of our sources inside multiple layers of mediation and how we are situated inside an information ecosystem that demands our active participation” (3–4).

As Martin explains, the new models of reading and research reveal that collaboration, interdisciplinarity, and behind-the-scenes work are critical to the project of research. Accordingly, each chapter of the book includes the title of one or two of the PPA’s “Collections” in brackets. Titles such as “How We Classify [Linguistic]” and “How We Argue [Original Bibliography]” reinforce the connection between Martin’s work as the author of a monograph, a widely accepted form of scholarship, and the collaborative work of building the PPA and the CDH, which supports researchers in creating exciting but often unacknowledged scholarly interventions.

“When humanities scholars do not cite or acknowledge the databases in which they encounter a digitized historical page (citing, instead, its print form in an archive they have never visited),” Martin explained, “they invisibilize the scholarly labor of turning that page into data; similarly, we do not acknowledge the scholarly interventions of creating digital scholarly sources in our outdated structures of tenure and promotion.”

Similarly, Martin notes that her involvement with the Historical Poetics reading group—the participants in which do not all identify as digital humanitists—and her contributions to building the PPA and CDH run parallel to each other both chronologically and thematically.

“Just as I don’t believe we can navigate the new information environment as literary critics and believe we are in any way alone, so too did I learn that I am able to come to understand the material mediations of nineteenth-century poetry only with a group of devoted colleagues” (16).

These values continue to inform Martin’s projects. In addition to directing the CDH, Martin is at work on two co-authored books: Data Work in the Humanities, with former CDH postdoctoral associate and Weld Fellow Zoe LeBlanc, now assistant professor in the School of Information Sciences at the University of Illinois Urbana-Champaign; and Walled Gardens, with CDH Project Manager Mary Naydan and Lead RSE Rebecca Sutton Koeser. She also serves as co-PI on the PLI-funded “Exercises in Literary Style” project with Associate Research Scholar and Perkins Fellow Wouter Haverals.

“I could not have helped to create the PPA without everyone past and present at the CDH,” Martin explained, “and I could not have argued in Poetry's Data that modern humanities research is fundamentally collaborative, and that we need to re-conceive it as such, without learning this first-hand from and with these same colleagues.”

Congratulations to our Digital Humanities Strategist, Grant Wythoff, on the publication of his book, A User’s Guide to the Age of Tech (University of Minnesota Press, 2025).

Wythoff’s book foregrounds users’ experiences to create what Wythoff calls a “media theory from below” (9). Central to Wythoff’s project is the language of “technique”—that is, “the way we do things, not just the tools we use to do them” (14). Focusing on the “embodied know-how of the end user” can help us see how users serve not just as the recipients but as the “agents of technological change” (9).

“Every day, people negotiate a unique and intimate syntax with their tools, tacitly debating things like the relative merits of usefulness and efficiency versus habit and sheer aesthetic joy,” Wythoff writes. “Those micro-level techniques don’t exist in a vacuum; in the aggregate, they add up to paradigm shifts in the history of technology through a series of wordless debates” (8–9).

At the same time, Wythoff emphasizes that the language of technology plays a critical role in illuminating “the imaginative space between tools and their users” (13). In the third chapter, for instance, Wythoff traces the history of the word “gadget.” Like many tech terms, Wythoff observes, “gadget” emerged from the world of seafaring (cf. ports and pirating!), but it proved especially significant because of its lack of specificity.

“What makes gadget unique as a term of art is its indeterminacy: sailors devised the word to mean anything at all, whatever you happened to be pointing at,” he writes. The word’s status as a “placeholder, an empty container” facilitated its changes in meaning (61).

Over the years, Wythoff argues, “gadgets have evolved from clever little trivialities or handy multitools into platforms that influence our politics, attention, relationships, and memories. In the process, a tool that was mapped onto gender (handymen; boys and their toys) now instead seems a marker of generation (screen-addicted millennials, who studies show actually use their phones less frequently than Generation Xers)” (66).

The importance of language to Wythoff’s project extends beyond the book’s argument. Wythoff noted that conversations with colleagues at the CDH helped him hone his ideas.

“The CDH is a community of people applying countless experimental methods, people who are trained in even more fields from across the humanities,” he explained. “All of these brilliant folks are thinking very carefully, in real time, about the impacts of emerging technologies on our world. . . . I benefitted from being part of this ecosystem of ideas, from hallway conversations and links shared, almost on a daily basis while writing my book.”

Wythoff’s book concludes with reflections on the rise of AI, the focus of the CDH’s current initiative, Humanities for AI.

In the epilogue, Wythoff imagines two ways that humans may react to a world increasingly dominated by AI—at the expense of humans themselves. In the first, which draws from an essay by Maggie Appleton, humans undertake a “high-stakes race between technique and tech: users devise novel techniques to stay one step ahead of tech as it eats the valuable new information users leave in their wake” (99–100). In the second, Wythoff writes, users opt out of the internet as we know it altogether, thus depriving AI of the new data it needs to operate.

What unites these two very different scenarios?

For Wythoff, it’s that users have the power to shape the future of technology—even in this most uncertain age of AI.

“They will refuse systems that extract technique in order to replace it, and they will pour their creative energies and trust into something different” (100).

This fall, the Center for Digital Humanities (CDH) continues its focus on "Humanities for AI" with the launch of a new project called Modeling Culture: New Humanities Practices in the Age of AI. While research and debate about artificial intelligence rapidly evolve, Modeling Culture turns attention toward what the humanities uniquely offer. It explores AI not only as a technology to critique, but as a new mode of inquiry for research and interpretation.

"AI is transforming how we teach, learn, and imagine knowledge," says Meredith Martin, CDH Faculty Director and Principal Investigator. "But humanists bring essential perspectives. Beyond asking what AI can do for our research, we must articulate what humanistic methods, histories, and critiques can contribute to AI development. Modeling Culture equips scholars with the resources to engage these questions directly, empowering us to shape the future of these tools rather than simply respond to them."

The project will unfold over the 2025-26 academic year in three interconnected components: a year-long faculty and graduate seminar, a public lecture series, and an open-access curriculum. Together, these initiatives provide a framework for thoughtfully testing, questioning, and integrating generative AI into the established traditions of humanistic study. Modeling Culture is generously funded by an AI Lab Seed grant, and with additional support from the Humanities Council and the Princeton Humanities Initiative.

A Seminar for Critical Discussion

The Modeling Culture seminar, led by CDH-affiliated and guest instructors, will convene monthly for eight sessions throughout the course of the academic year. Each session will explore a specific humanistic engagement with generative AI—from probing its interpretive limits to leveraging outputs for creative and pedagogical purposes, to developing new workflows for data curation.

Participants will also grapple with the broader challenges these tools present: the opacity of large language model architectures, biases embedded in outputs, and the complexities of incorporating AI responsibly into digital humanities research and teaching. Through methodological transparency, iterative experimentation, and ethical reflection, the seminar will demonstrate how humanists can engage with AI both creatively and critically.

Public Conversations on AI and Culture

Complementing the seminar, six public talks by visiting instructors will present new ideas in the field of cultural analytics to a broad Princeton audience. These presentations will illuminate the histories, theories, and practices shaping the intersection of AI and the humanities, exploring a wide range of topics from early modern print networks to questions of whether machines can truly "read" or "write" poetry, to investigations of literary style in an era of synthetic text.

Extending the Impact

The project reflects CDH's broader commitment to exploring how data-intensive methodologies can illuminate cultural history while questioning the assumptions embedded within those methods. After the conclusion of the seminar, the instructional team will develop a freely available curriculum that can be widely shared with scholars, departments, and institutions interested in a pedagogical framework for the humanities and AI.

Through this open-access resource, Modeling Culture will foster humanities-informed conversations about AI that extend far beyond Princeton's campus. The curriculum will provide other institutions with tested methodologies, ethical frameworks, and practical approaches for integrating generative AI into humanistic research and teaching. In this way, the project aims not simply to model one approach to AI in the humanities but to catalyze a broader transformation in how academic communities engage with these powerful new tools.

For more information and updates on Modeling Culture, visit:

We’re excited to announce that Paul Vierthaler, assistant professor of Chinese literature and interdisciplinary data science, has joined the Center for Digital Humanities as associate faculty director.

A specialist in late imperial Chinese literature and print history, Vierthaler came to Princeton last year from the College of William & Mary. His book project uses computational methods, such as natural language processing and machine learning, to explore how late imperial fiction and “quasi-histories” distort historical information.

“Paul will bring his unique perspective as a leading expert in East Asian Studies DH to the CDH, as well as his years of experience with collaborative computational humanities scholarship and teaching,” explained CDH Faculty Director Meredith Martin. “But more than all of that, we just feel lucky to have Paul among us; he's brilliant, truly engaged in the field, and an absolute pleasure to work with.”

Vierthaler quickly became part of Princeton’s digital humanities community. In addition to serving on the CDH executive committee, he collaborated with Anna M. Shields, Gordon Wu ’58 professor of Chinese studies and longtime CDH affiliate, on this summer’s China-Princeton Digital Humanities Workshop. The weeklong series of DH training sessions, co-sponsored by the CDH, brought together graduate students, postdocs, and junior faculty for sessions on topics from text analysis to databases to MARKUS and markup platforms.

As Associate Faculty Director, Vierthaler will build upon this work by contributing to the CDH’s strategic planning and participating in this year’s Modeling Cultures seminars. This fall, he will also add to Princeton’s computational and data humanities (CDH) course offerings by teaching two CDH-coded classes: an undergraduate course, EAS 307 / CDH 307: Digitally Detecting the Strange: Crimes, Ghosts, and Other Odd Things in Late Imperial China; and EAS 407 / CDH 407: Hacking Chinese Studies: An Introduction to Text Mining for Chinese Literature and Culture, which is open to both undergraduates and graduate students.

Vierthaler’s expertise in East Asian digital humanities will advance the CDH’s recent emphasis on multilingual DH, with initiatives including the African Languages in the Age of AI Speaker Series and the Digital Humanities for Hellenic Studies Summer Institute.

"I've spent my career up to this point using computational methods to study late imperial Chinese literature and print history, mostly focusing on works written between 1500 to 1800. As such, I work with material written in languages that have significantly different affordances than English and other Western languages, which tend to dominate the digital humanities landscape in North America and Europe,” Vierthaler explained. “At the Center for Digital Humanities, I am particularly excited to leverage this interest in underserved languages to collaborate with folks to help enhance the already very impressive work the Center is doing in multilingual DH.”

This past year, the Center for Digital Humanities celebrated its tenth anniversary with the theme “Humanities for AI.” Through this series of events, projects, and conversations, we explore how humanistic values and approaches are crucial to developing, using, and interpreting the field of AI.

As part of this initiative, we were thrilled to welcome award-winning writer Ted Chiang to Princeton on March 18 to present his talk “The Incompatibilities Between Generative AI and Art” with support from the AI Lab, Humanities Initiative, and Princeton Public Library. In this talk, he expanded on points from his essay “Why A.I. Isn’t Going to Make Art” in The New Yorker (August 2024). To delve deeper into topics such as artistic self-expression and the role of choice, as well as the tension between art and commerce, we invited Chiang to respond to a set of questions related to AI and its impact on humanities scholarship.

What does Humanities for AI mean to you?

The goal of universities is to produce graduates who can be more than just workers at widget factories, and studying the humanities is an essential part of that. Capitalism's goal is to turn the entire world into a widget factory, and AI is a powerful tool for achieving that. So I see Humanities for AI as an attempt to wrest the technology from the hands of capitalism and find uses for it other than extracting economic value from people.

In your opinion, has speculative fiction influenced the rise of generative AI?

Not directly. What we think of as generative AI only started around 2020 with programs like GPT-3 and DALL-E, and it wasn't something that even people working in AI had anticipated; they simply discovered that their programs had some unexpected capabilities and decided to lean into them. While there have been science-fiction stories about machine-generated fiction and art in the past — some of which seem eerily prescient in retrospect — I don't think anyone working in AI was aware of them or drawing inspiration from them.

If we zoom out from generative AI to consider AI more broadly, then I'd say speculative fiction has had a big role. The idea of the singularity — a point in time when machine intelligence exceeds human intelligence — was popularized by the science fiction writer Vernor Vinge. Vinge had an enormous influence on the Extropian community in the 1990s, and that community influenced AI research in the 2000s. I think it's also important to note that it was a non-fiction essay of Vinge's that was most influential, rather than his fiction. The practice of presenting fictional scenarios as non-fiction has now become the norm in Silicon Valley.

Do you envision scenarios where AI positively influences creative writing? What conditions do such possibilities require?

It's hard for me to imagine a scenario where AI helps writers do good work. Writing involves very little overhead; it's not like making a movie, where your budget determines what possibilities are available to you. You can write with a pencil and paper and do pretty much the same work as with a typewriter or a word processor. When you write, your medium is sentences, and I don't know what it would look like to have a technology that gives you greater control over sentences. Because of that, writing is relatively unaffected by advances in technology. This is also why I don't think the word processor has had a significant impact on creative writing; whatever changes we've seen in the novel over the last fifty years have probably been due to other cultural factors. I've read the claim that novels have gotten longer because of word processing, but I think even that has more to do with shifts in the publishing industry than with the increased ease of typing.

There might be certain creative possibilities opened up by explicitly using LLMs to write about LLMs, but I don't see that becoming a widespread practice. There's a form of visual art called scanography, which relies on the effects made possible by digital scanners. Without intending any insult, I think it's fair to say that scanography is a niche genre. I'd say that generative AI has comparable potential for creative writing.

What advice do you have for college students who face the prospect of using generative AI in their studies?

Everyone should think carefully about using generative AI simply because the technology is built on environmental destruction, labor exploitation, and IP theft. College students should think extra carefully about it because, even if those other issues were magically resolved, using generative AI is largely incompatible with the purpose of education. In the talk I gave, I said, "When you’re a student at a university, you should think of yourself as an athlete in training, and the job you'll do after you graduate is the sport you will compete in. You don’t know specifically which sport you will play, and neither do your professors. What your professors do know is that strength training will help you. That’s what essay writing is; it’s strength training for the brain. Using ChatGPT to write your essays is like bringing a forklift into the weight room; you are never going to improve your cognitive fitness that way." Let me expand on that. Building strength requires exertion; if anyone offers you an exercise program that involves no exertion at all, you know it's not going to be effective. The improvements that come from doing cognitive exercise are not as rapid as those that come from physical exercise, but they are just as real. Writing an essay is hard because it forces you to use your brain in ways you haven't before, and that is precisely why it's useful. Your job is not to turn in completed assignments; it's to learn how to think. Turning in completed assignments can help you learn how to think, but only if you're the one who completed them.

You ended your talk with a call for people to go out and create something meaningful to themselves or someone else. What is a creation you have read, seen, or experienced recently that has been meaningful to you?

The TV series ANDOR really impressed me. I don't particularly care about the STAR WARS universe; the only reason I tried this series was because Tony Gilroy was involved. In terms of craft, the series is a marvel; the dialogue, performances, production design, and music are all excellent. But completely separate from that, I think it's a remarkable depiction of what's involved in fighting fascism. Critics have said that one reason for the original STAR WARS' popularity was that, in the post-Vietnam era, it allowed Americans to feel good about themselves again by reminding them of "just wars" like the American Revolution or World War Two. What ANDOR does is more complicated and subversive. In the original movie, you could read the Empire as being a stand-in for Nazi Germany, but in ANDOR, it's hard for me to read the Empire as being anything other than a stand-in for the United States.

About Ted Chiang

Ted Chiang's fiction has won four Hugo Awards, four Nebula Awards, six Locus Awards, and the PEN/Malamud Award and has been reprinted in The Best American Short Stories. His first collection, Stories of Your Life and Others, has been translated into twenty-one languages, and the title story was the basis for the Oscar-nominated film Arrival. The New York Times chose his second collection, Exhalation, as one of the 10 Best Books of 2019. As a 2023 TIME100 Most Influential Person in AI, Chiang is described as “perhaps the world’s most celebrated living science-fiction author.”

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