Hypomnemata and the New Industrialization of Memory in GenAI

James E. Dobson
15 July 2026 (17:00 Berlin)

In 2025, large commercial GenAI chatbot vendors quietly introduced a new “memory” feature. “Memory,” in this context, refers to the inclusion of selected summaries of prior interactions alongside the current prompt in the model’s context window, producing the appearance of persistent state in a fundamentally stateless architecture. Through the industrial management of what I would term memory-as-context, chatbot applications implementing this memory feature blur the distinction between in-context learning and in-weights learning. By continually retrieving and reinserting prior interactions into new contexts, these applications create the appearance of ongoing adaptation and persistent personal memory, even though the underlying language model remains unchanged. This manufactured continuity encourages the perception of a chatbot personality, intensifies anthropomorphic interpretations of model behavior, and enables the construction of increasingly detailed user profiles that can become objects of information extraction and monetization. This talk takes up the open-source OpenClaw application as a case study for examining common processes for the management of memory. While open-source agentic applications like OpenClaw may expose a small number of sites for read-write activity, enabling users to selectively edit, insert, and delete the store of memories associated with their activity, the sheer volume of tokens generated and the mechanisms through which these applications consolidate past activities deskill and deauthorize their users. If the digital promised a loosening up of producer and consumer roles, the advent of endlessly recursive writing machines has terminated that once hopeful dream.

About the Speaker:

James E. Dobson is Associate Professor of English and Creative Writing at Dartmouth College, where he has been teaching in the humanities since 2012 and researching computational methods since 2003. His interests and publications span a wide range of topics, from accessing computational and data resources on large, distributed computing networks to autobiographical self-representation in American literature. Most recently, he has focused on computer vision, computational hermeneutics, and the history of machine learning and artificial intelligence.
 
He is the author of three books: Modernity and Autobiography in Nineteenth-Century America (Palgrave, 2017), Critical Digital Humanities (University of Illinois Press, 2019), and The Birth of Computer Vision (University of Minnesota Press, 2023). He is also co-author, with Rena J. Mosteirin, of the critical code study and poetic interpretation of the Apollo 11 Guidance Computer titled Moonbit (punctum books, 2019), and Perceptron (punctum books, 2025), a creative and critical account of the perceptron—one of the earliest and most successful machine learning devices—and its inventor, Frank Rosenblatt.