It is not lowering the bar to find better ways to demystify and explain things. In fact, I would say those who can explain it well understand it the best. Richard Feynman would be my best example.
Do you have any examples of places you felt like there was a lot of gatekeeping? Perhaps having studied mathematics I am a bit blind to the issue here and would like to learn more.
I agree making simple things sound complicated to appear more impressive is bad but there are limits. Even with Feynman he could only go so far, e.g. his interview about why questions and magnetism.
I am not thinking of intentional gatekeeping, but more of the kind where mathematicians build themselves their own island of concepts and notation with no thought of building a passageway for others to engage and make use of the theory.
I would find modern algebraic geometry highly useful as someone who works in computer graphics and computer vision, but much of the theory is akin to learning a new language and I don't get the sense that those who publish their work in this field care if I enter their world.
I do think in a lot of fields there is a lot of impact/influence to be had by people who are willing to do work to bridge different fields. I wonder to what degree this is because practitioners don't always see how their work could be used elsewhere.
I would say that it is lowering the bar to "find better ways to demystify and explain things." But there is no harm to this bar falling, because this is a bar for entry. There is a separate bar for making research discoveries (being credited for them, specifically), and that one should not be lowered, because it is a bar of standards.
We have seen the thing in programming. I'm not a gatekeeper, I love seeing more people to code. On the other hand, along the way, we lost the joy of the journey and only fixated at the destination.
Result is more software at lower quality. The reason is statistics. When you increase the population, you increase the population of every kind of programmer, and people who want the result are favored in most competitive sectors because corporations want something somewhat working yesterday.
...and here we are.
Now programmers talking about code quality is stoned en-masse. If it's somewhat working then it's good. Efficiency, resiliency, maintainability and sustainability is an afterthought. Some of my friends who loved debating programming language theory now don't even care about the code. They don't write it, just vibe, and they don't plan to come back to "older, caveman style of development".
Some universities are also adding fuel to the fire: They "prepare students for the job", not teaching the science, but the parts that corporations need for the job only.
Though, hardware was cheap and people were expensive, and now code is cheap and hardware is expensive now. We'll see.
The point I was trying to make was not "enjoying the process for the sake of it", but paying attention and spending effort on the journey created better software at the end.
When you look at older software, most of it was higher quality than the things we have today. A web site contained more information in a more readable way, more features in a smaller footprint. Same for native applications.
Now we slap what we found online together and calling it done. Everything is sparse, takes ages to load, centuries to submit and everything is so disconnected and async that some simple features are straight out impossible.
This is what fixating on the destination brought us. I dare you to download something you purchased 3 months ago via a 4096 character S3 link they have sent you, and double dare you to ask customer support for a new link. I'll bet that with a 80% chance they have no way to verify your serial number, even.
Have people completely forgotten how to read? I'm saying your analogy between software and math is completely, irreconcilably flawed. I don't need to read the rest of your screed because this is a thread about math not software.
Somebody said that lowering the bar is not good. Somebody else asked for examples, and I provided an example. So, if you want to be pedantic, that doesn't track well, because what I answered was not about mathematics.
If you want something about mathematics, computation is mathematics, as software is. So, my example tracks the same way in mathematics.
Finding solutions without understanding its parts or the path is equally detrimental to mathematics as it is detrimental to software.
Maybe you need to read a bit slower and think along the way. Using AI too much blunts critical thinking skills in some, as I read.
What was the end of the proof thing you mathematicians use, was it "Q.E.D."?
> computation is mathematics, as software is. So, my example tracks the same way in mathematics.
brother i already addressed this literally in my first response to you: the reason software went to shit is because it became commodified (ie a thing produced in a factory) not because it's computational nor because the bar got lowered. seriously read my whole original reply again and see whether you really disagree before just re-asserting your rant on SWE.
> Finding solutions without understanding its parts or the path
you didn't read the post at all did you? it's emphatically about deep understanding over blind results.
> Using AI too much blunts critical thinking skills in some, as I read.
Are you arguing that all the metal we have in our cars, buildings, airplanes is still being forged by hand? That that the furniture people are buying off Amazon is handmade? That stonework isn't primarily done these days with concrete pours?
>(which is that people who enjoy math will continue to be able to).
You posited that code is not like art, because it's primarily written for money and not for pleasure. But that's a stupid fucking argument, because there are plenty of crafts out there that are both done for money and pleasure (often by the same people!).
Half of modern academia, for one. Universities have turned into degree mills with the expectation that >50% of the population requires a college degree, regardless of whether they actually have any interest or need for one beyond doing it because it's a prerequisite for a good career, independent of whether said career actually uses the knowledge in any way.
Not that I actually agree that math was at the right level of gatekeeping. It definitely feels intentionally opaque beyond reason, and I think it's why LLMs are able to cut through the obfuscation and solve problems that maybe wouldn't actually have been considered quite so hard if mathematicians did a better job of making their work accessible.
It is not lowering the bar to find better ways to demystify and explain things. In fact, I would say those who can explain it well understand it the best. Richard Feynman would be my best example.
Do you have any examples of places you felt like there was a lot of gatekeeping? Perhaps having studied mathematics I am a bit blind to the issue here and would like to learn more.
I agree making simple things sound complicated to appear more impressive is bad but there are limits. Even with Feynman he could only go so far, e.g. his interview about why questions and magnetism.
I am not thinking of intentional gatekeeping, but more of the kind where mathematicians build themselves their own island of concepts and notation with no thought of building a passageway for others to engage and make use of the theory. I would find modern algebraic geometry highly useful as someone who works in computer graphics and computer vision, but much of the theory is akin to learning a new language and I don't get the sense that those who publish their work in this field care if I enter their world.
Ah that's fair.
I do think in a lot of fields there is a lot of impact/influence to be had by people who are willing to do work to bridge different fields. I wonder to what degree this is because practitioners don't always see how their work could be used elsewhere.
I would say that it is lowering the bar to "find better ways to demystify and explain things." But there is no harm to this bar falling, because this is a bar for entry. There is a separate bar for making research discoveries (being credited for them, specifically), and that one should not be lowered, because it is a bar of standards.
Examples, preferably academic?
We have seen the thing in programming. I'm not a gatekeeper, I love seeing more people to code. On the other hand, along the way, we lost the joy of the journey and only fixated at the destination.
Result is more software at lower quality. The reason is statistics. When you increase the population, you increase the population of every kind of programmer, and people who want the result are favored in most competitive sectors because corporations want something somewhat working yesterday.
...and here we are.
Now programmers talking about code quality is stoned en-masse. If it's somewhat working then it's good. Efficiency, resiliency, maintainability and sustainability is an afterthought. Some of my friends who loved debating programming language theory now don't even care about the code. They don't write it, just vibe, and they don't plan to come back to "older, caveman style of development".
Some universities are also adding fuel to the fire: They "prepare students for the job", not teaching the science, but the parts that corporations need for the job only.
Though, hardware was cheap and people were expensive, and now code is cheap and hardware is expensive now. We'll see.
this comparison makes little sense.
> we lost the joy of the journey and only fixated at the destination.
that's because you can make money with code and so it went the same way as everything else that's capitalized/commodified.
here a better comparison would be art which is generally still pursued on its own merits/pleasures.
The point I was trying to make was not "enjoying the process for the sake of it", but paying attention and spending effort on the journey created better software at the end.
When you look at older software, most of it was higher quality than the things we have today. A web site contained more information in a more readable way, more features in a smaller footprint. Same for native applications.
Now we slap what we found online together and calling it done. Everything is sparse, takes ages to load, centuries to submit and everything is so disconnected and async that some simple features are straight out impossible.
This is what fixating on the destination brought us. I dare you to download something you purchased 3 months ago via a 4096 character S3 link they have sent you, and double dare you to ask customer support for a new link. I'll bet that with a 80% chance they have no way to verify your serial number, even.
Have people completely forgotten how to read? I'm saying your analogy between software and math is completely, irreconcilably flawed. I don't need to read the rest of your screed because this is a thread about math not software.
I see.
Somebody said that lowering the bar is not good. Somebody else asked for examples, and I provided an example. So, if you want to be pedantic, that doesn't track well, because what I answered was not about mathematics.
If you want something about mathematics, computation is mathematics, as software is. So, my example tracks the same way in mathematics.
Finding solutions without understanding its parts or the path is equally detrimental to mathematics as it is detrimental to software.
Maybe you need to read a bit slower and think along the way. Using AI too much blunts critical thinking skills in some, as I read.
What was the end of the proof thing you mathematicians use, was it "Q.E.D."?
Q.E.D.
> computation is mathematics, as software is. So, my example tracks the same way in mathematics.
brother i already addressed this literally in my first response to you: the reason software went to shit is because it became commodified (ie a thing produced in a factory) not because it's computational nor because the bar got lowered. seriously read my whole original reply again and see whether you really disagree before just re-asserting your rant on SWE.
> Finding solutions without understanding its parts or the path
you didn't read the post at all did you? it's emphatically about deep understanding over blind results.
> Using AI too much blunts critical thinking skills in some, as I read.
irony
>here a better comparison would be art which is generally still pursued on its own merits/pleasures.
What about the crafts? Carpentry, blacksmithing, stonesmithing, etc. are all commodified yet people still pursue these for pleasure.
>this comparison makes little sense.
Stop gatekeeping what people find personally fulfilling.
> Carpentry, blacksmithing, stonesmithing
they're literaly not - do you know what the word artisanal means?
> Stop gatekeeping what people find personally fulfilling
wut? i can't even parse this in relation to what i wrote (which is that people who enjoy math will continue to be able to).
>do you know what the word artisanal means
https://www.merriam-webster.com/dictionary/artisan
Do you?
>they're literaly not
Are you arguing that all the metal we have in our cars, buildings, airplanes is still being forged by hand? That that the furniture people are buying off Amazon is handmade? That stonework isn't primarily done these days with concrete pours?
>(which is that people who enjoy math will continue to be able to).
You posited that code is not like art, because it's primarily written for money and not for pleasure. But that's a stupid fucking argument, because there are plenty of crafts out there that are both done for money and pleasure (often by the same people!).
Half of modern academia, for one. Universities have turned into degree mills with the expectation that >50% of the population requires a college degree, regardless of whether they actually have any interest or need for one beyond doing it because it's a prerequisite for a good career, independent of whether said career actually uses the knowledge in any way.
Not that I actually agree that math was at the right level of gatekeeping. It definitely feels intentionally opaque beyond reason, and I think it's why LLMs are able to cut through the obfuscation and solve problems that maybe wouldn't actually have been considered quite so hard if mathematicians did a better job of making their work accessible.
<pedant>28% of adult Americans</pedant>
66% in Japan. Who said anything about America?
You know, where most of the universities are.
And, who said anything about Japan? Confused.