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G.H. Parker's avatar

I saw a lot of AI boosters talking about that study with concern. Some seemed genuinely surprised by the findings and suggested they still don't believe them, even though they seem so obvious to you (and me).

While it is true that these people aren't actually stupid, it is also true that people are good at fooling themselves and justifying their preferences. People who enjoy using AI for whatever reason have an interest in seeing the technology as good and ignoring tradeoffs. This study might state the obvious, but an MIT study with brain scans is harder to ignore than just following the logic chain to a conclusion you dislike.

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Carsten B's avatar

(Ok, dmissing the "cookie" message leads to the long text one has written to disappear. I've learned something...let me rewrite it.)

I love your energy post, but I am genuinely puzzled about this one. Or, rather, I get the general gist and message you want to convey. However, I don't find the arguments convincing, at all.

Concerning the "obviousness" of GenAI loneliness: i) I am not sure I find the correlation (or causation) as obvious as you imply. Many people have made a similar argument concerning smartphones: "of course starting at a small screen all day is making people lonely". Well, except the studies investigating this show mixed results. If they had not, many people could have said something similar: "Duh, why I even study this". ii) Irrespective of the overall relation, and as I try to drill into my Philosophy of Science students, we really shouldn't only care about the direction of an effect, but also the effect size. To me it seems like the studies could actually speak to that, and might help the reader update their priors on how strong a correlation one should expect (+ all the other more nuanced findings in the studies). iii) Sure, the quote in question is superficial, but one can't include all nuances when talking to a journalist. In any case, I felt informed by the study.

Concerning MIT-brain study: i) I've worked with GenAI in education for a few years, offered a RAG to hundreds of students since January 2024, and done experimental studies in this field. I am genuinely not sure, that it is that obvious to (most?) students that using GenAI in ones work has such effects. More concretely, I am not sure that students realize that if you copy-paste several segments of text that was written by a chatbot, that that doesn't lead to some kind of learning. In other words, the study argues against a Matrix style "download" concept of learning, that I do think captures some discourse around learning. Now, the treatment is fairly extreme (and doesn't really cover a nuanced scenario) but that is quite usual in social science, that one begins with more extreme treatments, and then makes them more realistic along the way. In any case, I am quite confident that many students will feel informed when learning about this study, which is why I have written about it in a text aimed at students. ii) The MIT study involved interesting findings, such as homogenization, memory issues and it presented a solid theoretical framework in the form of cognitive load. Sure, the sample size was way too small, the EEG stuff is probably p-hacked (or an equivalent term) and the results are oversold, both by the authors and by the media / influencers. Nevertheless, it informed me (not that my priors moved that much). And I really don't think I am that stupid when it comes to GenAI :).

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