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

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Re: MIT Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

#471

Post by rozab »

This study itself and also the media coverage of it are shockingly bad. I wrote a bunch about it at the time and I don't really want to do that again but here is the low down:

- This is not a longitudinal study. Each partipant did 4 20 minute sessions. It just happens that the total study took 4 months. - The paper does not imply long term harm of any kind, they just measured brain connectivity during the short tasks. - It is not surprising that when asked to use an LLM to write an essay, partipants don't remember it. They didn't write it. - It is not surprising they showed less brain activity. They were delegating the task to something else. They were asked to. - I think the authors of the paper deliberately attempted to obscure this. Q7 on p30 is "LLM group: If you copied from ChatGPT, was it copy/pasted, or did you edit it afterwards?" This has been removed from the results section entirely, and other parts of the results do not match the supposed methodology. - The whole paper is extremely sloppy, with grammar mistakes, inconsistencies, and nonsensical charts. Check out Figure 29...

Re: MIT Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

#472

Post by bentt »

I believe this just based on my experience. I've also noticed that the rewards I feel from programming are stolen, and there's this conflicting feeling of accomplishment without the process. It's maybe a bit like taking mind-altering drugs in that they create reward artificially.

Much of what keeps me going with work is the reward loop. This changes it fundamentally and it's a bit frightening how compelling the actual productivity is, versus the psychological tradeoff of not getting the reward through the typical process of problem solving.

Re: MIT Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

#474

Post by [deleted] »

e3bc54b2 wrote: post #228
CuriouslyC wrote: post #189

Earlier quoted context omitted.

We're just moving up the abstraction ladder, like we did with compilers. I don't care about the individual lines of code, I care about architecture, code structure, rigorous automated e2e tests, contracts with comprehensive validation, etc. Rather than waste a bunch of time pouring over agent PRs I just make them jump over extremely high static/analytic hurdles that guarantee functionality, then my only job is to ide…

As the other comment said, LLMs are not an abstraction. An abstraction is a deterministic, pure function, than when given A always returns B. This allows the consumer to rely on the abstraction. This reliance frees up the consumer from having to implement the A->B, thus allowing it to move up the ladder. LLMs, by their very nature are probabilistic. Probabilistic is NOT deterministic. Which means the consumer is neve…

[deleted]

Re: MIT Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

#475

Post by oceanplexian »

e3bc54b2 wrote: post #228
CuriouslyC wrote: post #189

Earlier quoted context omitted.

We're just moving up the abstraction ladder, like we did with compilers. I don't care about the individual lines of code, I care about architecture, code structure, rigorous automated e2e tests, contracts with comprehensive validation, etc. Rather than waste a bunch of time pouring over agent PRs I just make them jump over extremely high static/analytic hurdles that guarantee functionality, then my only job is to ide…

As the other comment said, LLMs are not an abstraction. An abstraction is a deterministic, pure function, than when given A always returns B. This allows the consumer to rely on the abstraction. This reliance frees up the consumer from having to implement the A->B, thus allowing it to move up the ladder. LLMs, by their very nature are probabilistic. Probabilistic is NOT deterministic. Which means the consumer is neve…

> LLMs, by their very nature are probabilistic.

This couldn't be any more wrong. LLMs are 100% deterministic. You just don't observe that feature because you're renting it from some cloud service. Run it on your own hardware with a consistent seed, and it will return the same answer to the same prompt every time.

Re: MIT Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

#476

Post by oceanplexian »

bdhcuidbebe wrote: post #413
pmarreck wrote: post #405

Earlier quoted context omitted.

> LLMs, by their very nature are probabilistic I believe that if you can tweak the temperature input (OpenAI recently turned it off in their API, I noticed), an input of 0 should hypothetically result in the same output, given the same input.

That only works if you decide to stick to that exact model for the rest of your life, obviously.

The point is he said "by its nature". A transformer based LLM when called with the same inputs/seed/etc is literally the textbook definition of a deterministic system.

Re: MIT Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

#477

Post by CuriouslyC »

sarchertech wrote: post #414
CuriouslyC wrote: post #373

Earlier quoted context omitted.

This is doable, I have a multi-stage process that makes it pretty reliable. Stage 1 is ideation, this can be with a LLM or humans, w/e, you just need a log. Stage 2 is conversion of that ideation log to a simple spec format that LLMs can write easily called SRF, which is fenced inside a nice markdown document humans can read and understand. You can edit that SRF if desired, have a conversation with the agent about it…

Imagine that when you deploy you have an LLM that regenerates code based on your specs, since code is fungible as long as it fits the spec. Keeping in mind that I have seen hundreds to thousands of production errors in applications with very high coverage test suites? How many production errors would you expect to see over 5 years of LLM deployments.

Maybe more, but agents can also respond to errors much more quickly, and agents have the ability to manage small staged rollouts with monitoring to catch an issue before it goes global, so your actual downtime will be much better at the same time that you're producing code way faster.

Re: MIT Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

#478

Post by tomrod »

sarchertech wrote: post #440
tomrod wrote: post #419

Earlier quoted context omitted.

You'll need to specify the study, I see several candidates in my search, several that are quite older. Generally, yes, low N is unequivocally worse than high N in supporting population-level claims, all else equal. With fewer participants or observations, a study has lower statistical power, meaning it is less able to detect true effects when they exist. This increases the likelihood of both Type II errors (failing t…

The need for a large sample size is dependent on effect size. The study showed that 0 of the AI users could recall a quote correctly while more than 50% of the non AI users could. A sample of 54 is far, far larger than is necessary to say that an effect that large is statistically significant. There could be other flaws, but given the effect size you certainly cannot say this study was underpowered.

You would need the following cohort size per alpha level (currently 18) at a power level of 80% with an effect size of 50%:

0.05: 11 people per cohort

0.01: 16 people per cohort

0.001: 48 people per cohort

So they do clear the effect size bar for that particular finding at the 99% level, though not quite the 99.9% level. Further, selection effects matter -- are there any school-cohort effects? Is there a student bias (i.e. would a working person at the same age, or someone from a difficult culture or background see the same effect?). Was the control and test truly random? etc. -- all of which would need a larger N to overcome.

So for students from the handful of colleges they surveyed, they identified the effect, but again, it's not bulletproof yet.

Re: MIT Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

#479

Post by CuriouslyC »

jplusequalt wrote: post #463
CuriouslyC wrote: post #275

Earlier quoted context omitted.

Would that experience get eroded though? LLMs let me perform experiments (including architecture/system level) quickly, and build stress test/benchmark/etc harnesses quickly to evaluate those experiments, so in the time you can build human intuition with one experiment I've done 10. I build less intuition from each experiment, but I'm building broader intuition, and if I choose a bad experiment it's a small cost, but…

>Would that experience get eroded though? Yes. If you stop doing something, you get worse at it. There is literally no exception to this that I'm aware of. In the future where everyone is dependent on ever larger amounts of code, the possibility that nobody will be equipped to write/debug that code should scare you.

The amount of weightlifting a strength athlete needs to do to stay near their peak (but outside medal range) is ~15% of a full training workload. People can play instruments once a month and still be exceptional once the pathways are set down. Are you getting slightly worse at direct code jockeying? Sure, but not a lot, and you're getting superpowers in exchange.

Re: MIT Study Finds AI Use Reprograms the Brain, Leading to Cognitive Decline

#480

Post by kbelder »

oceanplexian wrote: post #475
e3bc54b2 wrote: post #228

Earlier quoted context omitted.

As the other comment said, LLMs are not an abstraction. An abstraction is a deterministic, pure function, than when given A always returns B. This allows the consumer to rely on the abstraction. This reliance frees up the consumer from having to implement the A->B, thus allowing it to move up the ladder. LLMs, by their very nature are probabilistic. Probabilistic is NOT deterministic. Which means the consumer is neve…

> LLMs, by their very nature are probabilistic. This couldn't be any more wrong. LLMs are 100% deterministic. You just don't observe that feature because you're renting it from some cloud service. Run it on your own hardware with a consistent seed, and it will return the same answer to the same prompt every time.

I think 'chaotic' is a better descriptor than 'probabilistic'. It certainly follows deterministic rules, unless randomness is deliberately injected. But the interaction of the rules and the context the operate in is so convoluted that you can't trace an exact causal relationship between the input and output.
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