Dennis Yi Tenen is an associate professor of English and Comparative Literature at Columbia University. His teaching and research happen at the intersection of people, texts, and technologies. A long-time affiliate of Columbia’s Data Science Institute and formerly a Microsoft engineer and a Berkman Center for Internet and Society Fellow, his code runs on millions of personal computers worldwide. Tenen received his doctorate in Comparative Literature at Harvard University under the advisement of Professors Elaine Scarry and William Todd. A co-founder of Columbia’s Group for Experimental Methods in Humanistic Research and the editor of the On Method book series at Columbia University Press, he is the author of Plain Text: The Poetics of Computation (Stanford University Press, 2017). His recent work appears on the pages of Modern Philology, New Literary History, Amodern, boundary2, Computational Culture, and Modernism/modernity on topics that include literary theory, the sociology of literature, media history, and computational narratology. His next book concerns the creative limits of artificial intelligence.
Dennis Yi Tenen
Associate Professor, English & Comparative Literature, Columbia University
Participant In These Roundtable Discussions
Sat
Oct 15th
2022
Oct 15th
2022
Watch
Coding and the New Human Phenotype
This conference explores the concept of life, knowledge, and experience through the lens of “code,” examining how meaning is encoded, transmitted, and transformed across biological, digital, and cultural systems. Through five roundtables, it investigates how we reconstruct the past, navigate authenticity in a digital world, interpret fiction and ideas, engage with AI-generated language, and consider the possibility that reality itself may be fundamentally computational—together asking what is gained, and what may be lost, as code increasingly mediates our understanding of the world.
Sun
Oct 16th
2022
Oct 16th
2022
Watch
Coding and the new Human Phenotype: Are Natural Language Generators for Real?
This roundtable investigates the implications of AI systems capable of generating human-like language and behavior. It asks how these systems challenge our understanding of intelligence, agency, realism, and ethical responsibility.