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. […]
Norman
The key point with letters of recommendation is to acquire a reputation for being reliable. Once you have that, you have everything you need.
Jamie
Reliability is very important but when people don’t know who you are then you also have to include phrases that help readers to position you. Things like `of the 100 students I have supervised over the past 20 years’ show not only the comparitor group but also indicate your reliability.
About the stiffness of the language: since the subject of the reference is often legally required to have access to the letter people are careful about what they write so as not to offend. People who read the letters get used to seeking metasyntactic cues such as: does the recommender speak more about the importance of the research project than the person who conducted the work, do they conclude with hearty or unqualified recommendation? Do they say that they would hire this person if they applied for a job?
(P.S.: I’m sure *you* wrote a great letter.)