Today’s meeting about copyright and copying at Bergen Kunsthall (“deledagen”) has been critisised for only having male presenters (in the BB mailing list today, archives are subscribers only). The organisers answer that they asked two women who couldn’t come, and they pull the standard line, you know, “Vi kan ikke /lage/ kvinnelige debattanter, de m selv stille opp.” (We can’t /make/ female debaters, they have to turn up themselves.) So knowing that it is hard as an organiser or editor to find and catch contributors from outside of one’s own circle, I’m trying to think which women in Norway should have been asked. Any suggestions?


Discover more from Jill Walker Rettberg

Subscribe to get the latest posts sent to your email.

2 thoughts on “women, copying, sharing

  1. Cassandra

    If it’s O.K. for a male to comment, I believe one can begin to better understand many of the male-female issues, after reading “Brainsex”. As its male/female joint authors say, there’s nothing new in it. It merely pulls together, in an easily read form, a range of material which is usually ignored, but is essential to anyone wanting to understand current “difficulties”.

  2. Jill

    Oh, I hated Brainsex. Except the bit that said that I was better at multi-tasking because I’m a woman 😉

    Watching my daughter and her classmates I’ll agree there are differences between men and women that probably aren’t merely to do with socialisation – but socialisation certainly increases the differences, and I do think that a balance between genders and perspectives is desirable in discussions…

    It’s not easy to ensure such balances though. (Nice to see you again, Cassandra 😉

Leave A Comment

Recommended Posts

AI STORIES

AI-generated stories have longer endings than human stories

My colleague Jessica Witte has just shared a preprint where she compared the emotional arcs of the stories we generated using gpt-4o-mini to those of human-authored (pre-2022) stories from the subreddit r/WritingPrompts, conveniently gathered in this dataset. She found a distinct difference in the endings of the LLM-generated stories: both […]

How to peer review a paper in 2026

Dorothy Bishop, a psychologist, wrote a useful list of what reviewers need to look out now that so many papers are bad science that looks good thanks to LLMs. Read her whole blog post, she explains it well, but here’s a brief version because I’m pretty sure we’ll be needing […]

“So what if it was ChatGPT? It *could* have been true!”

I recently read a good article on the different kinds of truth a language model operates with by Luke Mann, Liam Magee and Vanicka Arora, Truth Machines: Synthesizing Veracity in AI Language Models, but despite its lovely typology of truths (consensus, correspondence, coherence and pragmatic) it doesn’t help me with […]

AI STORIES

AI shimmer and sparkle

I have this hunch that sparkles and glow and shimmer are somehow a point in the latent spaces of LLMs that have more connections than you would expect. Perhaps their connotation to magic and to the unknown matches some of the mystique of genAI? Or perhaps these words are used […]

Don’t do a systematic review if you’re in the humanities

This paper is a great example of why you probably shouldn’t use a systematic literature review for a theoretical and conceptual research question like “How does artificial intelligence affect the perception of authenticity and aura in art?” However, if you’re looking for an annotated list of 48 recent articles about […]