We’re seeing a lot of students, teachers, and scientists produce more, and worse, outputs because of improper AI use. It’s possible to use it better: Have it imitate a critic. Learning and creativity come from getting criticism and experiencing friction.
We found that when knowledge workers intentionally use AI to challenge their ideas – to generate friction – they can significantly improve their performance. Previous research on human-AI collaboration for loan evaluations had similar results.
A study I was not involved with found that creative writers produce better copy when they use AI as a sounding board rather than to ghostwrite.
So I think you’ve landed on the problem that I have with student use, and that the article has with scientist default use. It is very bad for folks to use AI to try to do the knowledge work directly, yet people are making this mistake constantly. YSK: it’s much better when you make AI increase the friction of knowledge work. (note neither are claiming that this use is particularly good; we’re doing damage control.)
I definitely notice sloppy thinking when I see it in someone else’s review of my papers. You certainly pick it up when you read climate-change-denialists. Experts are great at noticing sloppy thinking when it disagrees with them. That is the relationship you want with genAI if you are using it for knowledge work. Make it disagree with you, so you notice where it is very sloppy (and sometimes where you’ve been sloppy because the bad thinker is kinda right).
Yeah. Agree in theory. I’m a bit sus on the adversarial AI approach in practice, because most LLMs seem to produce a lot of sycophancy, and I think that’s a far too easy trap to fall in to.
I do think there are some practical uses, such as reducing availability bias by asking it “is there anything I’ve forgotten to consider in this thing I wrote?” AFTER you’ve done the thinking and writing. But I think the temptation to use it for generative purposes is pretty huge, and likely to suck a lot of people in.