Huh. Hand hurts. So much for live blogging. Will take a break.
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Professor and Co-Director of the Center for Digital Narrative at the University of Bergen
Professor and Co-Director of the Center for Digital Narrative at the University of Bergen
Huh. Hand hurts. So much for live blogging. Will take a break.
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On May 1st Canvas announced a security breach, and then yesterday the system was hacked. The login page was replaced by a ransom note: if universities don’t pay up by 12 May, student data will be released. Here’s what the login page looked like yesterday: Way back in 2015, when […]
My German is pretty dodgy, so when I first saw Heimatstrom on Bluesky, shared by Roland Meyer, a professor of visual culture at Universität Zürich’s Digital Society Initiative, I misinterpreted it and thought it was a far-right campaign. But no, Heimatstrom is a group of left-wing environmentalists using fascist AI […]
There’s a new ad for the train between Stavanger and Oslo in Norway that uses a line from Arnulf Øverland’s famous anti-fascist poem Du må ikke sove (“You must not sleep”). Du må ikke sove, you must not sleep, the ad says. And then it flips it, jovially, joda, bare […]
I just signed a petition calling for Norwegian universities to use research expertise on AI when deciding how to implement it, rather than having decisions be made mostly administratively. , If you are a researcher in Norway, please read it and sign it if you agree – and share with anyone else who might be interested. The petition was written by three researchers at UiT: Maria Danielsen (a philosopher who completed her PhD in 2025 on AI and ethics, including discussions of art and working life), Knut Ørke (Norwegian as a second language), and Holger Pötzsch (a professor of media studies with many years of research on digital media, video games, disruption, and working life, among other topics). This is not about preventing researchers from exploring AI methods in their research. It is about not uncritically accepting the hype that everyone must use AI everywhere without critical reflection. It is about not introducing Copilot as the default option in word processors, or training PhD candidates to believe they will fall behind if they do not use AI when writing articles, without proper academic discussion. Changes like these should be knowledge-based and discussed academically, not merely decided administratively, because they alter the epistemological foundations of research. Maria wrote to me a couple of months ago because she had read my opinion piece in Aftenposten in which I called for a strong brake on the use of language models in knowledge work. She was part of a committee tasked with developing UiT’s AI strategy and was concerned because there was so much hype and so few members of the committee with actual expertise in AI. I fully support the petition. There are probably some good uses for AI in research, but the uncritical, hype-driven insistence that we must simply adopt it everywhere is highly risky. There are many researchers in Norway with strong expertise in AI, language, ethics, working life, and culture. We must make use of this expertise. This is also partly about respect for research in the humanities, social sciences, psychology, and law. Introducing AI at universities and university colleges is not merely a technical issue, and perhaps not even primarily a technical one. It concerns much more: philosophy of science, methodological reflection, epistemology, writing, publishing, the working environment, and more. […]
Grammarly is a full on AI plagiarism machine now, generating text, citations (often irrelevant), “humanizing” the text to avoid AI checkers and so on. If you’re an author or scholar, they also have been impersonating and offering “feedback” in your name. Until yesterday, when they discontinued the Expert Review feature due to a class action lawsuit. Here are screenshots of how it worked.
A summary of yesterday’s Critical AI Theory Reading Group discussion of Ryan Heuser’s article about LLM-generated poetry, with a discussion of whether LLMs normalise or idealise their training data.