LILINTERNET shares AI art reading list
- On September 1, LILINTERNET posted an AI-art reading list on X that grouped art history, machine vision, operational images and ongoing artist research. - The list named Kathryn Brown’s “Artificial Intelligence and Art History,” Trevor Paglen’s “How to See Like a Machine,” and Hito Steyerl’s “Medium Hot.” - Readers can find the post on LILINTERNET’s X account, where the thread links books and related projects.
LILINTERNET posted a reading list on X on September 1 that pulled together a specific corner of the AI-and-art debate: art history, machine vision, operational images, and current work by artists and philosophers. The post named three books directly — *Artificial Intelligence and Art History* from Liverpool University Press, Trevor Paglen’s *How to See Like a Machine: Images After AI*, and Hito Steyerl’s *Medium Hot* — and pointed readers toward ongoing projects in the same field. ### Why does this reading list matter beyond “AI art” as a catchall term? The September 1 post is notable because it does not center image generators, prompts or copyright fights. Instead, the books it names sit in a longer argument about how images are made, sorted, read and used by machines as well as people. That places the thread closer to debates in visual culture, surveillance studies and digital art history than to consumer AI product chatter. (artmarketstudies.org) Liverpool University Press’s *Artificial Intelligence and Art History*, edited by Kathryn Brown, is described by distributors and library listings as a volume on tensions and opportunities in human-machine “dialogues” about visual art, with contributors addressing machine learning, computer vision and whether algorithmic analysis changes human seeing. (artmarketstudies.org) ### What does “machine vision” mean in the books LILINTERNET highlighted? Trevor Paglen’s *How to See Like a Machine: Images After AI* argues that images are increasingly made by machines and for machines, not only for human viewers. Publisher material for the book says Paglen examines computer vision, surveillance and generative AI as part of a changed visual environment in which pictures are processed, classified and acted on by technical systems. (utpdistribution.com) Recent coverage of Paglen’s book has framed it in those terms. Newcity wrote on August 31 that the book takes readers into the transformation of image-reading and image-making in recent decades, while Aesthetica described Paglen’s broader practice as focused on AI, data sets and surveillance. ### What are “operational images,” and why do artists keep returning to them? (versobooks.com) Hito Steyerl is one of the artists most associated with the term “operational images,” which generally refers to images produced to do a job inside a system rather than to be contemplated as pictures in the traditional sense — for example, in tracking, targeting, recognition or automated decision-making. LILINTERNET’s post grouped Steyerl’s *Medium Hot* with Paglen’s book, signaling that the reading list is about image systems and infrastructure as much as about aesthetics. (art.newcity.com) The pairing is consistent with how critics have described the field. The Brooklyn Rail wrote that Paglen’s book belongs to a cohort of recent artist writing on AI and images that includes Steyerl’s 2025 book *Medium Hot: Images in the Age of Heat*. ### Why include art history in a conversation that sounds technical? (brooklynrail.org) Kathryn Brown’s work shows why art history has moved into this discussion. Brown’s project page lists *Artificial Intelligence and Art History: Looking at Images in an Algorithmic Culture* among recent AI-and-art publications, and the TIAMSA book discussion announcement from April identified the Liverpool University Press volume as a forum for discussing how visual art is studied when computational systems are also “looking” at images. (brooklynrail.org) That framing shifts the question from whether AI can make art to how institutions, archives, scholars and artists now encounter images through databases, classifiers and machine-readable formats. The books in LILINTERNET’s post all touch that shift from different angles. ### What should a reader look at next from this thread? The September 1 post itself is the next stop, because LILINTERNET said the reading list also links ongoing projects by artists and philosophers working on machine vision and operational images. (kathrynbrownarthistory.com) The named books provide the frame; the linked projects appear to extend that frame into current practice. (artmarketstudies.org) (searchworks.stanford.edu)