CASK2026: Full Schedule

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14:00 EDT

Thursday June 11, 2026 14:00 - 14:30 EDT

Introduction to AI, LLM and Archives
Held during International Archives Week, whose theme — Archives for Justice: Rights, Memory and Futures — asks what the records we keep are for in an age of artificial intelligence, this talk offers a working answer from inside the systems and cybernetics community.
It surveys what AI and large language models are actually doing in archives today — transcription, description, retrieval — and the genuine fight now underway over whether collections may be used to train models at all. But it judges that landscape with our own instruments. Drawing a line from Frank Burns's 1981 ethics of influence to Mick Ashby's Ethical Regulator Theorem, it treats every archive and its AI as a regulator of memory: six requisites make such a system effective, but only three more — transparency, integrity, and ethics — make it good, and those three must be deliberately specified, or lost by default.
Along the way it shows working examples, including knowledge graphs and teaching modules built to keep every claim traceable to its source. It closes on the shift from merely keeping heritage to activating it, and on what a distributed community of custodians might build together next.

Sources referenced

International Council on Archives — International Archives Week 2026, “Archives for Justice: Rights, Memory & Futures” (8–12 June 2026). https://ica.org

Mick Ashby — The Ethical Regulator Theorem and the Law of Inevitable Ethical Inadequacy (ISSS 2017; published 2020). https://journals.isss.org/index.php/proceedings61st/article/view/3075

Roger Conant & W. Ross Ashby — “Every good regulator of a system must be a model of that system” (1970). https://www.theisticscience.com/papers/tree/BioRegulation/Conant-IJSS1970.pdf

Frank Burns — “An Ethical Paradigm for Subtle Influence” (1981) — your own archive; the nine-point operating paradigm. https://coexploration.org/metasystems

Robert Rosen — Anticipatory Systems (1985) and Life Itself (1991); the modelling relation. https://model.coexplorer.org

US National Archives and Records Administration (NARA) — AI use-case inventory. archives.gov/ai

Library of Congress with GBH — American Archive of Public Broadcasting, FixIt+ transcript-correction platform. https://blogs.loc.gov/thesignal/2026/04/aapb-sorenson-interview/

Society of American Archivists — knowledge-graph-augmented generative AI for cultural heritage (February 2026). https://www2.archivists.org/sites/all/files/Gnanasekaran_Marciano_paper.pdf

Library of Congress & Joshua Sternfeld — “Content Authenticity and Provenance in the Age of Artificial Intelligence” (February 2026). https://blogs.loc.gov/thesignal/2026/04/content-authenticity-and-provenance-in-the-age-of-artificial-intelligence-a-call-to-action-for-the-libraries-archives-and-museums-community/

Archives and Records Association (UK) — AI Preparedness Guidelines for Archivists. https://www.archives.org.uk/ai-preparedness-guidelines-for-archivists

University of Virginia Archival AI Protocol — Leo S. Lo (2025); “no access without control.” https://library.virginia.edu/news/2026/protecting-what-remains-introducing-uva-archival-ai-protocol

Authors Alliance — “AI & Access to Knowledge” series; “Library and Archives 101: AI and the False Promise of Control” (2026). https://www.authorsalliance.org/2026/03/16/library-and-archives-101-ai-and-the-false-promise-of-control/