Rob Fitzpatrick from Georgia Tech’s Game Lab is presenting on characters and morality. Three dimensions of dramatic dimension – games (in contrast) heavily oriented towards action. Psychological and social data is mostly absent. However morality is becoming more important/popular. In single player games you can measure everything the player does.

Crono Trigger (1995): after a couple of hours, there’s a trial against you where the NPCs argue that you are morally reprehensible based on how you play. If you eat an old man’s lunch cos it’s a powerup at the trial he’ll speak against you.This isn’t done later in the game, simply because (one assumes) the data would just be too much. Also the verdict of the trial has no effect, you always go to jail.

Ultima Online (1995): First successful MMPORG. All objective single player data still exists. The player and other players ideas about the character are outside the game but affect the way you play the game, and are attached to the character. The death of Lord British. Rainz was unknown before he killed Lord British, but becamse known to EVERYONE afterwards – he was a celebrity, everyone loved him (until he was banned). Obviously changed his gaming experience hugely, but outside of the game system. UO has a reputation system based on e.g. how many players you’ve killed, use evil magic. Using evil magic matters to the world, but there’s another system measuring how many players you’d murdered – this was implemented to show the difference between characters who steal and characters who are player-killers, so players can react to things that affect them most.

Encoding character morality:

  • granularity (not just good/evil but murderer/protector, thief/ ?, deceiver/honest etc)
  • chaos & consistency (is the character consistent in morality?)
  • forgiveness (there’ll always be a way where what you did stops mattering in time

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Academics in Norway: Sign this petition asking for research-based discussions of how to use AI in universities

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. […]

screenshot of Grammarly - main text in the middle, names of experts on the left with reccomendations and on the right more info about the expert review feature
AI and algorithmic culture Teaching

Grammarly generated fake expert reviews “by” real scholars

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.