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. […]
Francois Lachance
The excerpt on _trashing_ leads me to wonder if two types of argumentation are not being conflated in the term: “ad hominem” and “reductio absurdum”. The one questions the credibility of the source (i.e. the person conveying the information or line of thought); the other is concerned with the what (i.e. how well [or not] the argumentation is presented usually by testing the universality of its application).
Interesting the use of the first person pronoun in the discours crafted by Professor Bal invites the reader to identify with the position of having been both sender and receiver of trashing behaviour. Rare will be the case where one finds an “I” that boasts of a generous and fair interchange — the boasting itself would undermine the effect. The route to cultivating a less trash-oriented culture of rigourous intellectual intercourse would be perhpas to something akin to Montaigne’s Essays where the form of illustration is not in the first person confessional mode but in the mode of reporting X’s behaviour towards Y — nobel actions set alongside less than noble.
Very often “going for the jugular” as trashing is sometimes called involves exposing the great weakness of an argument. However there is a fine line between going for and slicing! The generous critic will contextualize the perceived weakness if not motivate its appearance. In short, the generous critic tells a story and projects a future. The critic sets the stage for recycling.