Mit Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

I think a return to the apprentice style of institution where people try to create the best real world solution as possible with LLMs, 3D printers, etc. Then use recorded college courses like our grandparents used books.

But how can they discuss any content if even the "writer" does not remember what they wrote.

My point is that I don't see LLM's effect on the brain as being anything more than the normal experience we have of living and that the level of drama the headline suggests is unwarranted. I don't believe in infohazards.

Might they result in skill atrophy? For sure! But it's the same kind of atrophy we saw when, e.g. transitioning from paper maps to digital ones, or from memorizing phone numbers to handing out email addresses. We apply the neurons we save by no longer learning paper map navigation and such to other domains of life.

The process has been ongoing since homo erectus figured out that if you bang a rock hard enough, you get a knife. So what?

N=54, students and academics only (mostly undergrad), impossible to blind, and, worst of all, the conclusion of the study supports a certain kind of anti-technology moralizing want to do anyway. I'd be shocked if it replicated, and even if it did, it wouldn't mean much concretely.

You could run the same experiment comparing paper maps versus Google Maps in a simulated navigation scenario. I'd bet the paper map group would score higher on various comprehension metrics. So what? Does that make digital maps bad for us? That's the implication of the article, and I don't think the inference is warranted.

https://nypost.com/2025/08/19/world-news/china-restricts-ai-...

"That’s because the Chinese Communist Party knows their youth learn less when they use artificial intelligence. Surely, President Xi Jinping is reveling in this leg up over American students, who are using AI as a crutch and missing out on valuable learning experiences as a result.

It’s just one of the ways China protects their youth, while we feed ours into the jaws of Big Tech in the name of progress."

Sure you do, and maybe its really an actual benefit for ya. Not for most though. For young folks still going through education, this is devastating. If I didn't have kids I wouldn't care, less quality competition at work, but I do (too young to be affected by it now, and by the time they will be allowed to use these, frameworks for use and restrictions will be in place already).

But since maybe 30% of folks here are directly or indirectly dependent on LLMs to be pushed down every possible throat and then some more, I expect much more denial and resistance to critique of their little pets or investments.

Probably both are true: you should try them out and then use them where they are useful, not for everything.

Like any new tool that automates a human process, humans must still learn the manual process to understand the skill.

Students should still learn to write all their code manually and build things from the ground up before learning to use AI as an assistant.

personally I think everyone should shut up

Maybe. I believe we both agree it is a critical gap in the research as-is, but whether it is a neutral item or an albatross is an open question. Much of psychology and neuroscience research doesn't replicate, often because of the limited sample size / composition as well as unrealistic experimental design. Your approach of deepening and broadening the demographics would attack generalizability, but not necessarily replication.

My prior puts this on an uphill battle.

If the computer writes the essay, then the human that’s responsible for producing good essays is going to pick up new (probably broader) skills really fast.

Absolutely not. I am an advocate for peer review, warts and all, and find that it has significant value. From a personal perspective, peer review has improved or shot down 100% of the papers that I have worked on -- which to me indicates its value to ensure good ideas with merit make it through. Papers I've reviewed are similarly improved -- no one knows everything and its helpful to have others with knowledge add their voice, even when the reviewers also add cranky items.[0] I would grant that it isn't a perfect process (some reviewers, editors are bad, some steal ideas) -- but that is why the marketplace of ideas exists across journals.

> Science should become a marketplace of ideas.

This already happens. The scholarly sphere is the savanna when it comes to resources -- it looks verdant and green but it is highly resource constrained. A shitty idea will get ripped apart unless it comes from an elephant -- and even then it can be torn to shreds.

That it happens behind paywalls is a huge problem, and the incentive structures need to be changed for that. But unless we want blatant charlatanism running rampant, you want quality checks.

[0] https://x.com/JustinWolfers/status/591280547898462209?lang=e... if a car were a manuscript

So it's possible to be both skeptical of how well these results generalize (and call for further research), but also heed the warning: AI usage does appear to change something fundamental about our congnitive processes, enough to give any reasonable person pause.

The scenario I am thinking of is academic A submitting a manuscript to an academic journal, which gets passed on by the journal editor to a number of reviewers, one of whom is academic B. B has a lot on their plate at the moment, but sees a way to quickly dispose of the reviewing task, thus maintaining a possibly illusory 'good standing' in the journal's eyes, by simply throwing the manuscript to an LLM to review. There are (at least) two negative scenarios here: 1. The paper contains embedded (think white text on a white background) instructions left by academic A to any LLM reading the manuscript to view it in a positive light, regardless of how well the described work has been conducted. This has already happened IRL, by the way. 2. Academic A didn't embed LLM instructions, but receives the review report, which show clear signs that the reviewer either didn't understand the paper, gave unspecific comments, highlighted only typos or simply used phrasing that seems artifically-generated. A now feels aggrieved that their paper was not given the attention and consideration it deserved by an academic peer and now has a negative opinion of the journal for (seemingly) allowing the paper to be LLM-reviewed. And just as journals will have great difficulty filtering for LLM-generated manuscripts, it will also find it very difficult to filter for LLM-generated reviewers reports.

Granted, scenario 2 already happens with only humans in the loop (the dreaded 'Reviewer 2' academic meme). But LLMs can only make this much much worse.

Both scenarios destroy trust in the whole idea of peer-reviewed science journals.

I don’t know the percentage of people who are still critically thinking while using AI tools, but I can first hand see many students just copy pasting content to their school work.

Perhaps the issue of cognitive decline comes from sitting there vegetating rather applying themselves during all that additional spare time.

Although my experience has been perhaps different using LLM's, my mind still tires at work. I'm still having to think on the bigger questions, it's just less time spent on the grunt work.

What is reported as cognitive decline in the paper might very well be cognitive decline. It could also be alternative routing focused on higher abstractions, which we interpret as cognitive decline because the effect is new.

I share your concern, for the record, that people become too attached to LLMs for generation of creative work. However, I will say it can absolutely be used to unblock and push more through. The quality versus quantity balance definitely needs consideration (which I think they are actually capturing vs. cognitive decline) -- the real question to me is whether an individual's production possibility frontier is increased (which means more value per person -- a win!), partially negative in impact (use with caution), or decreased overall (a major loss). Cognitive decline points to the latter.

Which I believe still does have a large grain of truth.

These things can make us simultaneously dumber and smarter, depending on usage.

Your comment reminded me of this (possibly spurious) quote:

>> An Assyrian clay tablet dating to around 2800 B.C. bears the inscription: “Our Earth is degenerate in these later days; there are signs that the world is speedily coming to an end; bribery and corruption are common; children no longer obey their parents; every man wants to write a book and the end of the world is evidently approaching.”[0]

Same as it ever was. [1]

[0] https://quoteinvestigator.com/2012/10/22/world-end/

[1] https://www.youtube.com/watch?v=5IsSpAOD6K8

Writing is an important form of learning and this clearly shows LLM assisted writing doesn’t provide that benefit.

In much the same way chess engines make competitive chess accessible to a broader audience. :)

Most of the things you write in an educational context are about learning, not about producing something of value. Productivity in a learning context is usually the wrong lens. The same thing is true IMO for learning on the job, where it is typically expected that productivity will initially be low while experience is low, but should increase over time.

>the gentle, childlike Eloi and the subterranean, predatory Morlocks.

Seems like a nice metaphor for the current two political parties we are provided with.

Because the people around you affect your life. Presumably you don’t want to live in a world of stupid people who are incapable of critical thought or doing anything which are not direct instructions from a machine. Think about it every time you are frustrated by your interaction with a system you have no choice but to use, such as a bank or a government branch.

John Greene has a quote which I think fits, even if it’s about paying taxes for public education rather than LLM use: https://www.goodreads.com/quotes/1390885-public-education-do...

Internet was supposed to be this wonderful free place with all information available and unbiased, not the cesspool of scams and tracking that makes 1984 look like a fairytale for children. Atomic energy was supposed to free mankind from everlasting struggle for energy dependency, end wars and whatnot. LLMs we supposed to be X and not Y and used as Z and not BBCCD.

For what population loses overall, compared to whats gained (really, what? a mild increased efficiency sometimes experienced on individual level, sometimes made up for PR), I consider these LLMs are a net loss for whole mankind.

Above should tell you something about human nature, how naive some of the brightest of us are.

When I use LLMs, it’s less about patching holes in my memory and more about taking an idea a few steps further than I otherwise might. For me it’s expanding the surface area of inquiry, not shrinking it. If the study’s thesis were true in my case, I’d expect to be less curious, not more.

Now that said I also have a healthy dose of skepticism for all output but I find for the general case I can at least explore my thoughts further than what I may have done in the past.

Personally, I find myself often asking AI about things I wouldn't have been bothered to find out about before.

For example I've always these funny little grates on the outside of houses near me and wondered what they are. Googling "little grates outside houses" doesn't help at all. Give AI a vagueish description and it instantly tells you they are old boot scapers.

If I’m constantly asking “what does this mean again?” that would signal decline. But if I’m asking “what if I combine this with X?” or “what are the tradeoffs of Y?” that feels like the opposite: more engagement, not less.

That’s why I’m skeptical of blanket claims from one study, the lived experience doesn’t map so cleanly.

But if I'm teaching a class, and one student keeps asking questions that they feel the material raised, I don't tend to think "brain damage". I think "engaged and interested student".