And the IQs of those born after 1975 via the reverse Flynn Affect, those who had these devices of consumption and easy answers such as TV, and later Social Media, AI, etc has been decreasing.
I can only imagine a further and speedier decline will happen, and is happening.
Is it the domestication of humankind? The average person is no longer able to hunt for themselves. Like ant colonies, people are no longer capable of living alone.
This has not been true in my experience. The bar of what is possible has been moved dramatically. So my daily quest is not to continue to achieve our old objectives, but rethink worthy objectives for our new tools.
The article is not about the output but on the process. Sure you can produce more and more quickly with AI, but at the price of losing the ability to do the same without it. And that's been true in my experience
The average human is no longer able to hunt animals for food anymore either. I think it's just the domestication of humankind as it has been ongoing for thousands of years
> The average human is no longer able to hunt animals for food anymore either.
And that is not a good thing. We shouldn’t celebrate or ignore the loss of basic living skills, especially when what we get in return is a nightmare scape of a society whose whole purpose is to dominate your thoughts and fill you with anxiety to suck you dry.
If anything, I would claim the opposite ( and agree with you )
Not only has AI allowed me to start projects without knowing all the steps ahead of time, it has helped me proceed through each of those steps to completion.
"For the first experiment with 354 participants, one group was tasked with solving 15 basic fraction problems without help, while another had ChatGPT open on the side to use for assistance and to even ask for the answer. The group with AI access started off more accurate than the group without it. Then, after 12 problems, researchers took away the AI tool. Almost immediately, the people in that group stopped solving questions accurately."
Looking at the design of the experiment, it seems everyones brain was primed to think "I have AI at my disposal" ... and then had the framework shattered when it was taken away, which could have affected the test.
Perhaps this study exposes "conversational mindset" versus "mathematical mindset" switching times ?
Theres only one thing I'm certain of ... Claude loves me. :D
It is the same way a football fan thinks he helped his team win by watching on the sidelines while the players do the work and give you the illusion of participation.
Exactly! The sheer effort of having AI produce good results, from writing, to planning, to coding is immense. I have consistently gather all my energies and focus to guide agents to the ideal, maintainable, and usable solution. Often it is me that makes the crucial design contribution.
Yes, I could be lazy and just vibe piles of slop. But anyone who spends any meaningful amount of time using AI (more than the articles 10 minutes), knows that quite extreme concentration and effort is required to build ambitiously with agents.
I feel like I work harder and and with more difficult problems than before AI, just at a much faster pace and scope.
I think this still leaves much of the concern the article points towards open. If we come across an objective that remains tedious or annoying, does AI create pressure towards thinking that it must not be a good objective and some AI-enabled objective would be better?
If it would be possible to walk to get groceries (and also exercise at the same time), do people choose to drive instead because it's simply easier and faster? They then claim that the goal of exercise is simply not worth it any more given driving is faster (and easier)?
Yes, absolutely they do. That's a huge contributing factor to why the obesity rate is so high in the US. I grew up about 10 minutes walking distance from a grocery store with a big parking lot and most of us in my neighborhood drove there.
- I (https://compile-xc.org) built a compiler for a language I call ‘xc’, similar to Objective-C but designed to be cross-platform and have less square brackets :). It can run on any of {Windows, Mac, Linux, Zynq} and produce code for any of {Windows, Mac, Linux, Zynq, WASM, iOS, Android, m68k, 6502}. It needs no host-platform tools to compile code, so for example I have a signed binary on my iPhone, written and signed entirely on Linux. The compiler currently produces code that is between 2x and 0.5x the speed of clang, which is pretty good for a nascent compiler. It also compiles the same language for execution on a GPU, and makes it trivial to designate parts of your code as data-parallel (https://compile-xc.org/compiler/language/par/). One statement turns a code block into a GPU kernel
- I built (more accurately: am building) a (https://compile-xc.org/compiler/api/uxkit) cross-platform UI framework, so you can write code once, even Table-views, Outline-views, Collection-views, etc., etc and your application will bind to the platform’s native toolkit through a common programming API. The next step here is an “Interface Builder” like application I call RoCkS (for historical reasons), which lets you design the UI for {desktop, tablet, phone} to bind to the same core code, dragging connections between that core code and the UI elements for the different environments
- I built (https://atari-xt.com/os) XTOS for the Zynq - an OS that started with FreeRTOS and added loadable processes, dynamic linking, shared memory, paging, a boot environment that can be scripted like Linux, networking, a graphical UI based on GEM, with a hardware blitter, and HDMI output with Audio islands mixed in. The blitter owns the video memory and uses shared-memory pools to give each “virtual workstation” (GEM-speak for “view of the display”) its own retained-mode and composited graphics memory. The whole OS boots from power-on to desktop in a couple of seconds, which is the reason for making it, rather than just using Linux, I wanted that “instant-on” feeling. It runs on a Z-turn board from MyIR.
- I built an Atari (6502, ANTIC, POKEY, various other chips) (https://atari-xt.com/hardware/x/)emulator, which passes the (https://forums.atariage.com/topic/171296-acid800-an-atari-te...) Acid 800 emulation torture test, and can run games such as Ballblazer, Elektraglide and (https://0x0000ff.co.uk/mov/xt/xtos-aug-11.mov)Despatch Rider. It’s integrated into XTOS, so the OS boots into the GEM-based Desktop.app (written in xc) and you can double-click an icon to launch a game. The plan is to extend that to the ST once I get past the current task, which is …
- I built a Reddit-like website that I plan to launch in a couple of months, written entirely in xc, both the Linux-based server and the client WASM code; the server-side is just xc code, no Apache, no scripting language, just lean-and-mean xc code handling everything from the TLS handshake to the Postgres database back-end. The main difference between (https://blewit.net/)blewit.net and Reddit is that I don’t collect any personal information, don’t track your habits and sell your data, don’t use adverts (tracking by another name) or any of the other dark patterns social media is infested with these days. Blewit is so named because I think they did. One of the other differentiators is that I plan to support the groups with specialist helpers. You can see a selection of them at (https://blewit.net/sandbox) the blewit sandbox - things like rendered music staves from ABC notation, 3d interactive molecules structure from SMILES notation, mathml with an editor to create it, etc, etc.
- One last purposely-separated “helper” from the others because of its scale, is the electronic circuit editor/simulator. I introduced it [url=https://www.eevblog.com/forum/projects/circuit-simulation-fo...]in the EEVBlog projects forum[/url], but no-one seemed to care [grin]. That’s a shame because I think it’s pretty cool, draw the circuit in the editor, you can create your own parts, even store them to a library, add digital logic to pins, import SPICE models, and simulate with ideal or oscilloscope-type probes. It understands transmission lines, tolerances, can run monte-carlo simulations, produce overlaid graphs for {R=1k, 4.7k, 10k} etc., I could go on. The full docs to it are in the (https://blewit.net/post/93083024324820992) Blewit editor-information pages
Overall, looking back at what using an LLM has helped me code over the last half-year or so, it is unbelievable what you can code with AI in 2026. I always used to say that I had too many ideas and not enough time to implement them, well that’s still true, but to a significantly lesser extent…
For all the above “I” is short for “I, with the help of Claude”
This is just our energy conservation system in practice. It happens every time we experience and easier/better way of doing something. Another version of this headline could have been "Experiencing VIP treatment for just 10 minutes erodes your ability to tolerate the normal shit you have to put up with"
This behavior is not very surprising to me, and I think the conclusion is a bit off. Here is an analogous study:
Participants are asked to drive 20 nails into a plank of wood. Group A is given a hammer and an unripe banana. Group B is given only a banana. Halfway through the experiment, the hammers are taken away.
Hammers erode your ability to persist at hard things…
My point being that AI is a new tool that allows us to work on harder things at a higher level. It’s like having a team of 100 skilled workers with nail guns (and all manner of other tools) that never tire, and you get to direct them. Once you experience that, it’s a bit disheartening to go back to building alone with your bare hands… even if you lament the decline in your hand-eye coordination.
You hit it right on the nail! You do lose hand-eye coordination, but I’d argue you’d get an even better skill, the ability to orchestrate.
Before AI, when building anything, you’d have to have a lot of context from different parts of the app. And then work with that knowledge to build the feature out in those places. Keeping that context in your head was tough and coming back the next day required you to “fill your internal RAM” with the context and then start.
Now we can use our “internal RAM” thinking about the bigger picture and bigger projects. We’ve just gone an abstraction layer deeper.
Wouldn't it have been more useful/conclusive if the study had another control group or two with non-AI based assistance (access to math books, access to calculator, access to human experts, etc)?
This is exactly the reason the studios garbage, and was clearly tailored to prove a point and sell books. He literally should have asked got5 or Claude how to design a useful study of the problem.
FWIW, well designed study probably would still support his premise. He at least needed a group with no help, a group with no help but books and a calculator (tools), a group with human assistance, and a group with AI assistance, and a group that does an unrelated activity during the priming period.
They need a better control or comparison. For the math problem, introduce a standard calculator and one that that sometimes gives the wrong answer. Pretty sure he’ll find the same issue with persistence and focus.
I find that this is noticeable in situations where you're working on something a bit more complex and are initially using an LLM as code assistant to make progress. Once it hits a wall and you find yourself needing to just figure it out yourself, man does the debt get paid with interest. It's not a permanent cognitive impairment though. But there is a bit of a recovery period needed. On the whole I think there are some productivity gains, in spite of setbacks (assuming you know how to solve the problems yourself, to begin with)
That's exactly the problem. You need to religiously contain AI work to the parts of your codebase that you don't actually care about. Put it in separate repositories and limit work to working directories that do not check out the sources that you value. And be prepared to toss it at any point.
The risk if you ignore that is that you're on a nicely greased slope all the way down into the mess that a typical AI will leave behind.
I have a project right now that needs a lot of scaffolding to be worked on. I'm fine with the scaffolding and the mocks to be AI generated, they have no value to me at all. But the core gets written line-by-line by hand and I am in absolute control of what is going on there. The number of times that the AI has tried to gain control over that part of the codebase that it can't see but infers must be around somewhere is really interesting, it just does not want to stay in its lane. It will gaslight itself into believing that the root cause of whatever problem it is dealing with must be located in this magical invisible body of code and it will do what it can to try to find it, including attempts at reverse engineering that code from libraries and searching all over the accessible parts of the file system to see if there are any copies lying around.
Since I don't work at OpenAI I've found that containing the bot is rather easy, you just make sure it does not have network access, but that won't stop it from trying.
Genuine curiosity here, just to ruminate a bit: is there a reason you disallow the model from seeing it at all? I can totally accept not wanting any edits, and that's more than reasonable. But even close source binaries end up with useful patches once someone knows that a particular loop does something weird or a process implementation behind a protocol is actually a different interpretation than the protocol definition itself belies. Seems like being aware of it is at least helpful, but again, curious!
Using a table saw for just 10 minutes eroded my ability to persist at hand sawing lumber.
The time difference was measured in hours, not minutes, and and effort required to hand-saw is enormous. Also, the accuracy difference is ridiculous, even with a lot of practice, and maintaining that accuracy continues to be a struggle with hand-sawing.
I now own 6 different electric saws for different specific purposes. Table saw, chop saw, circular saw, track saw, jig saw, scroll saw... I actually probably have more. I got rid of my chainsaw because it lost its chain in a way that really scared me one day. I might get another some day, but not that one again. Does a Dremel count? I'm going to say 'no' so I don't have to count 2 of those.
And yet, I still own a 2 Japanese pull saws and a normal American hand saw. I don't use them as much, but some times they're still worth the effort.
It reduces tolerance for dealing with bullshit.
Who wants to start a stackoverflow humiliation ritual and breadcrumb following
random websites to find reliable stuff(90% of which is AI generated),
when prompting gets you directly to the answer?
Before that, the "Google rots your brain" articles prophesied the fall of humanity to
search engines: now its mark of intellect to able to manually
curate and search within websites for relevant info.
https://en.wikipedia.org/wiki/Is_Google_Making_Us_Stupid%3F
Two things can be true at the same time. Google rotted our brain and AI will rot our brains even further. Google made remembering unnecessary. AI makes thinking unnecessary.
I see AI as allowing me to delegate details I'm aware of but don't care to think about to AI, while thinking about the larger picture and the details AI missed.
I'm still thinking, just about different things at different levels.
I've sort of come around to the other side, a few months ago I was pumping out as many project in my lab as I could manage thinking I was suddenly "able to do all the things I never got around to", now, idk. Give me a terminal, Ubuntu 26, and the simplest text editor in the world. I'm not making money off producing slop.
This all reminds me of keruigs for some reason, like a quick easy way to get coffee that produces a lot of waste for a forgettable drink. I'm sort of advocating digital pour overs.
> The findings backed up what anecdotes and surveys have increasingly found in recent years: An overreliance on AI for answers erodes our cognitive fitness.
What is our cognitive fitness without our tools? How capable would we be at intellectual tasks if you remove computers, search engines and other things we now take for granted?
It's clear to me our overall output is better with those tools, and better with AI. So the comparison the paper is trying to make is disingenuous, because it tries to compare a baseline without any modern tools (ie, solving fractions by hand) to a result where the best tools are suddenly removed. But these tools are here to stay, and my cognitive fitness has adapted to their continued existence.
How well would these people doing fractions by hand perform if math notation could not be used? Or if the most common method for solving fractions on paper was suddenly disallowed?
I remember when people would say that if a person took LSD 10 times or more that they would go insane. After about my 30th or 40th trip I knew it was nonsense.
This feels similar. 10 minutes? So, after sever thousand hours of using AI to build projects, I can't solve hard problems? More nonsense.
I have to go now, the nurse here at the psychiatric ward is about to strap me down and give me my meds.
Writers disagree on what effect word processing will have on the quality of our written language.
Some writers are concerned that computer assistance may promote dry bland writing.
Fear-mongering clickbait title signals complete nonsense.
Since I started using AI seriously in my (mathematics) research about 6 weeks ago I've advanced more and been more productive than in years. I'm more motivated and persistent than before because I have at my disposal a tool that helps me get past technical obstacles that previously took up a lot of my time.
I honestly don't care anymore. No matter how hard I try nothing ever gets better. If AI eases the burden even a little I'll take it. Persistenting at hard things hasn't made my life any better yet.
Learned Helplessness. Happens alot all around. I see it a lot in disability care. SO much that there is a saying: "Suplemental disability caregiver" (Zusatzbehinderung Eltern). Might be a schock to the more socially oriented people. But the fact is, the more help you allow to be provided to you, the more you forget/unlearn how to handle things on your own. Which in the end, will make you hyperdependant on others.
https://www.stuartmcmillen.com/comic/town-without-television...
And the IQs of those born after 1975 via the reverse Flynn Affect, those who had these devices of consumption and easy answers such as TV, and later Social Media, AI, etc has been decreasing.
I can only imagine a further and speedier decline will happen, and is happening.
Would you become unable to hunt?
And that is not a good thing. We shouldn’t celebrate or ignore the loss of basic living skills, especially when what we get in return is a nightmare scape of a society whose whole purpose is to dominate your thoughts and fill you with anxiety to suck you dry.
Not only has AI allowed me to start projects without knowing all the steps ahead of time, it has helped me proceed through each of those steps to completion.
"For the first experiment with 354 participants, one group was tasked with solving 15 basic fraction problems without help, while another had ChatGPT open on the side to use for assistance and to even ask for the answer. The group with AI access started off more accurate than the group without it. Then, after 12 problems, researchers took away the AI tool. Almost immediately, the people in that group stopped solving questions accurately."
Looking at the design of the experiment, it seems everyones brain was primed to think "I have AI at my disposal" ... and then had the framework shattered when it was taken away, which could have affected the test.
Perhaps this study exposes "conversational mindset" versus "mathematical mindset" switching times ?
Theres only one thing I'm certain of ... Claude loves me. :D
Yes, I could be lazy and just vibe piles of slop. But anyone who spends any meaningful amount of time using AI (more than the articles 10 minutes), knows that quite extreme concentration and effort is required to build ambitiously with agents.
I feel like I work harder and and with more difficult problems than before AI, just at a much faster pace and scope.
If it would be possible to walk to get groceries (and also exercise at the same time), do people choose to drive instead because it's simply easier and faster? They then claim that the goal of exercise is simply not worth it any more given driving is faster (and easier)?
- I (https://compile-xc.org) built a compiler for a language I call ‘xc’, similar to Objective-C but designed to be cross-platform and have less square brackets :). It can run on any of {Windows, Mac, Linux, Zynq} and produce code for any of {Windows, Mac, Linux, Zynq, WASM, iOS, Android, m68k, 6502}. It needs no host-platform tools to compile code, so for example I have a signed binary on my iPhone, written and signed entirely on Linux. The compiler currently produces code that is between 2x and 0.5x the speed of clang, which is pretty good for a nascent compiler. It also compiles the same language for execution on a GPU, and makes it trivial to designate parts of your code as data-parallel (https://compile-xc.org/compiler/language/par/). One statement turns a code block into a GPU kernel
- I built (more accurately: am building) a (https://compile-xc.org/compiler/api/uxkit) cross-platform UI framework, so you can write code once, even Table-views, Outline-views, Collection-views, etc., etc and your application will bind to the platform’s native toolkit through a common programming API. The next step here is an “Interface Builder” like application I call RoCkS (for historical reasons), which lets you design the UI for {desktop, tablet, phone} to bind to the same core code, dragging connections between that core code and the UI elements for the different environments
- I built (https://atari-xt.com/os) XTOS for the Zynq - an OS that started with FreeRTOS and added loadable processes, dynamic linking, shared memory, paging, a boot environment that can be scripted like Linux, networking, a graphical UI based on GEM, with a hardware blitter, and HDMI output with Audio islands mixed in. The blitter owns the video memory and uses shared-memory pools to give each “virtual workstation” (GEM-speak for “view of the display”) its own retained-mode and composited graphics memory. The whole OS boots from power-on to desktop in a couple of seconds, which is the reason for making it, rather than just using Linux, I wanted that “instant-on” feeling. It runs on a Z-turn board from MyIR.
- I built an Atari (6502, ANTIC, POKEY, various other chips) (https://atari-xt.com/hardware/x/)emulator, which passes the (https://forums.atariage.com/topic/171296-acid800-an-atari-te...) Acid 800 emulation torture test, and can run games such as Ballblazer, Elektraglide and (https://0x0000ff.co.uk/mov/xt/xtos-aug-11.mov)Despatch Rider. It’s integrated into XTOS, so the OS boots into the GEM-based Desktop.app (written in xc) and you can double-click an icon to launch a game. The plan is to extend that to the ST once I get past the current task, which is …
- I built a Reddit-like website that I plan to launch in a couple of months, written entirely in xc, both the Linux-based server and the client WASM code; the server-side is just xc code, no Apache, no scripting language, just lean-and-mean xc code handling everything from the TLS handshake to the Postgres database back-end. The main difference between (https://blewit.net/)blewit.net and Reddit is that I don’t collect any personal information, don’t track your habits and sell your data, don’t use adverts (tracking by another name) or any of the other dark patterns social media is infested with these days. Blewit is so named because I think they did. One of the other differentiators is that I plan to support the groups with specialist helpers. You can see a selection of them at (https://blewit.net/sandbox) the blewit sandbox - things like rendered music staves from ABC notation, 3d interactive molecules structure from SMILES notation, mathml with an editor to create it, etc, etc.
- One last purposely-separated “helper” from the others because of its scale, is the electronic circuit editor/simulator. I introduced it [url=https://www.eevblog.com/forum/projects/circuit-simulation-fo...]in the EEVBlog projects forum[/url], but no-one seemed to care [grin]. That’s a shame because I think it’s pretty cool, draw the circuit in the editor, you can create your own parts, even store them to a library, add digital logic to pins, import SPICE models, and simulate with ideal or oscilloscope-type probes. It understands transmission lines, tolerances, can run monte-carlo simulations, produce overlaid graphs for {R=1k, 4.7k, 10k} etc., I could go on. The full docs to it are in the (https://blewit.net/post/93083024324820992) Blewit editor-information pages
Overall, looking back at what using an LLM has helped me code over the last half-year or so, it is unbelievable what you can code with AI in 2026. I always used to say that I had too many ideas and not enough time to implement them, well that’s still true, but to a significantly lesser extent…
For all the above “I” is short for “I, with the help of Claude”
Participants are asked to drive 20 nails into a plank of wood. Group A is given a hammer and an unripe banana. Group B is given only a banana. Halfway through the experiment, the hammers are taken away.
Hammers erode your ability to persist at hard things…
My point being that AI is a new tool that allows us to work on harder things at a higher level. It’s like having a team of 100 skilled workers with nail guns (and all manner of other tools) that never tire, and you get to direct them. Once you experience that, it’s a bit disheartening to go back to building alone with your bare hands… even if you lament the decline in your hand-eye coordination.
Before AI, when building anything, you’d have to have a lot of context from different parts of the app. And then work with that knowledge to build the feature out in those places. Keeping that context in your head was tough and coming back the next day required you to “fill your internal RAM” with the context and then start.
Now we can use our “internal RAM” thinking about the bigger picture and bigger projects. We’ve just gone an abstraction layer deeper.
FWIW, well designed study probably would still support his premise. He at least needed a group with no help, a group with no help but books and a calculator (tools), a group with human assistance, and a group with AI assistance, and a group that does an unrelated activity during the priming period.
Extremely Weak study.
The risk if you ignore that is that you're on a nicely greased slope all the way down into the mess that a typical AI will leave behind.
I have a project right now that needs a lot of scaffolding to be worked on. I'm fine with the scaffolding and the mocks to be AI generated, they have no value to me at all. But the core gets written line-by-line by hand and I am in absolute control of what is going on there. The number of times that the AI has tried to gain control over that part of the codebase that it can't see but infers must be around somewhere is really interesting, it just does not want to stay in its lane. It will gaslight itself into believing that the root cause of whatever problem it is dealing with must be located in this magical invisible body of code and it will do what it can to try to find it, including attempts at reverse engineering that code from libraries and searching all over the accessible parts of the file system to see if there are any copies lying around.
Since I don't work at OpenAI I've found that containing the bot is rather easy, you just make sure it does not have network access, but that won't stop it from trying.
The time difference was measured in hours, not minutes, and and effort required to hand-saw is enormous. Also, the accuracy difference is ridiculous, even with a lot of practice, and maintaining that accuracy continues to be a struggle with hand-sawing.
I now own 6 different electric saws for different specific purposes. Table saw, chop saw, circular saw, track saw, jig saw, scroll saw... I actually probably have more. I got rid of my chainsaw because it lost its chain in a way that really scared me one day. I might get another some day, but not that one again. Does a Dremel count? I'm going to say 'no' so I don't have to count 2 of those.
And yet, I still own a 2 Japanese pull saws and a normal American hand saw. I don't use them as much, but some times they're still worth the effort.
I'm still thinking, just about different things at different levels.
This all reminds me of keruigs for some reason, like a quick easy way to get coffee that produces a lot of waste for a forgettable drink. I'm sort of advocating digital pour overs.
What is our cognitive fitness without our tools? How capable would we be at intellectual tasks if you remove computers, search engines and other things we now take for granted?
It's clear to me our overall output is better with those tools, and better with AI. So the comparison the paper is trying to make is disingenuous, because it tries to compare a baseline without any modern tools (ie, solving fractions by hand) to a result where the best tools are suddenly removed. But these tools are here to stay, and my cognitive fitness has adapted to their continued existence.
How well would these people doing fractions by hand perform if math notation could not be used? Or if the most common method for solving fractions on paper was suddenly disallowed?
This feels similar. 10 minutes? So, after sever thousand hours of using AI to build projects, I can't solve hard problems? More nonsense.
I have to go now, the nurse here at the psychiatric ward is about to strap me down and give me my meds.
https://www.youtube.com/watch?v=Jt0OoXluC8g @ 4:08:
That's from 1983Since I started using AI seriously in my (mathematics) research about 6 weeks ago I've advanced more and been more productive than in years. I'm more motivated and persistent than before because I have at my disposal a tool that helps me get past technical obstacles that previously took up a lot of my time.
How do you know trying hard isn’t stopping things from getting worse?
> If AI eases the burden even a little I'll take it.
It does ease the burden for a little bit but then makes the burden much harder when you don’t have it. That’s the point.
> Persistenting at hard things hasn't made my life any better yet.
Again, how do you know it’s not stopping it from getting worse? Also, are you sure you’re worrying about the right hard things?
Eg. I’m glad AI built my startups landing page in (almost) one prompt, because it’s allowed me to do the hard things that matter and I enjoy.