The fact that the author is using PowerBI as the example makes me think they are completely oblivious of the actual impact and utility LLMs have in other fields such as programming. Claiming it's useless and that anything it outputs is "markedly inferior to that of a human doing the same task" is an absurd basis to use for their argument.
It’s also just false. The good LLMs already produce output far better than the average programmer in most domains.
People like to talk about code as craft and art but the vast majority of the code that was written has always been mediocre at best. LLMs already beat it.
A focused experienced skilled programmer can do better but the market niche for that kind of code is actually small. Most commercial code just has to be good enough to accomplish a business need.
If you think of LLMs as statistically averaging machines and think of human programmer skill as a bell curve, it helps understand the different experiences with LLMs of different people. Those on the left hand side of the skill curve will see an uplift, those on the right hand side will experience degradation.
The more pertinent question in my mind is.. why does it still matter? Your customers don’t care about elegant code, they are about working products. There is some relation to good code and good customer experience e.g in terms of performance, but in general your customers won’t feel the impact from poor code. That assumes both pieces of code are functional though, and you do need to babysit LLMs to make sure it actually remains functional.
I do feel that a lot of pessimists I hear keep banging away about hallucinations and untrustworthy outputs. It makes me think they’re willfully ignorant of the progress since they tried ChatGPT 3 several years ago and were underwhelmed.
I’m happy to engage in discourse on the impact and risks to environment, society, jobs, mental health, etc. There’s plenty of room for thoughtful exploration there.
The one thing I have no patience for is that LLMs produce nothing of value or have no technical worth.
People who understand computers and those who do not.
I have to keep reminding myself though, many of those pessimists are people “getting paid to not understand” as the saying goes.
It took 30 seconds with that Davinci model to predict where we are today, where we’ll be next year, and the eventual destruction if not outright extinction of humanity as we know it. Maybe the future is so grim many are simply in the denial stage still.
"The first point is the question of whether an LLM can do work not markedly inferior to that of a human doing the same task or not. This one is debatable. An LLM absolutely cannot produce work to the highest human standards, or even a good human standard at the moment, and it's unlikely that it ever will."
This could have been fine maybe two years ago, but saying that in the era when LLMs are solving Millenium Prize Problems is incredibly obnoxious. All those opinionated "AI articles" feel like ragebait at this point.
GPT-4 felt like a slightly dim but still very useful intern.
GPT-6.1 (and Opus 5.5, etc.,) is a solid mid-career pro who can produce outputs very much on par with "good human standards" -- and, in some cases, far better than that.
Whatever in-house dev model they're using at OAI/Anthropic is, by all accounts, legitimately superhuman and capable of solving outstanding technical and mathematical problems with three hours of "Pro thinking."
OP's complaint is foolish, it reads like somebody who has never even used these things and has no idea what their capabilities actually are.
> who can produce outputs very much on par with "good human standards"
“Can produce”. Is doing a lot of heavy lifting there. It can, but then they also regularly write truly bafflingly bad code that no decent experienced dev would ever produce.
I’ll give you a few examples from last week. I had claude whip up a Kafka consumer. After a lot of back and forth I was pretty confident it worked and then I decided to dig into the code. I spotted some real head scratchers.
When starting up the consumer it wanted to pass a specific rebalance strategy, but then it realized that the library it was using didn’t support that strategy, so it needed to use the default.
Instead of just deleting the config option (and maybe leaving a comment), it created a function that removed that key from the map and used it like:
Then I started looking at the tests. They looked good but then I realized it wanted to be able to test without Kafka so what it had done was make multiple public functions that were mostly duplicates the real functions
except that they didn’t call the Kafka library. Then it just tested those instead.
Another frontier model reviewer was supposed to prevent that kind of thing but it didn’t catch it either.
I had 10 public functions that were only called in tests throughout the whole project. Essentially the tests were useless because they weren’t actually testing anything.
Clearly current frontier models are useful. And maybe they produce code that is better than the median dev by many metrics. But I don’t think they are anywhere near consistently producing better quality than a say a 70the percentile dev with 10 years experience.
And even when the quality is better than the median dev, I’m finding that the bugs are not the kind of thing that humans or LLMs are good at spotting.
> An LLM absolutely cannot produce work to the highest human standards
yep. This is the choice quote.
Even most humans cannot produce work to the highest human standards. The fact is, most work does not need to be done to the highest human standards, it simply needs to be done to the lowest possible standard that someone would pay for, at the cheapest price.
The consumer chooses the cheapest price. Look at sweat shops, look at chinese manufacturing, look at offshoring. All of these produces an inferior product, and yet they are what gets the most profit and overwhelmingly the largest market share of consumer purchases.
yep. This is the choice quote.
Even most humans cannot produce work to the highest human standards. The fact is, most work does not need to be done to the highest human standards, it simply needs to be done to the lowest possible standard that someone would pay for, at the cheapest price.
TFA:
The first point is the question of whether an LLM can do work not markedly inferior to that of a human doing the same task or not. This one is debatable. An LLM absolutely cannot produce work to the highest human standards, or even a good human standard at the moment, and it's unlikely that it ever will. Most human work, however, is not done at a good standard. At best it's mediocre, and at worst it's downright horrible. The bulk of human knowledge work done in an awful of settings, then, is unfortunately more or less interchangeable with that of an LLM (seriously, so much human work is just awful: I wish I could say otherwise). On this point, then, LLMs probably pass the criterion.
I'd recommend that you take 15->30 minutes and read the entire essay. It's a good read.
It's so tiresome. I'm going to stop getting into these threads altogether soon. There's nothing to discuss with the ones who treat it like a religious belief. I keep thinking that they'll just try some of the tools and see reason, but you can't rationalize with the irrational.
I wish people who felt this way would just go use the tools they hate so much before passing judgement. I think many of them used it once, in a much worse form, many years ago and not since. Judging these things by the standards of 3 months ago is unfair, let alone the standards of 3 years ago.
> The technology can, in volume of adequate output or in quality of output, overwhelmingly outclass what alternative technologies can do. A moderate improvement isn't really enough to force inevitability: it has to be a massive difference.
> Now we come to the question of whether or not the difference that LLMs bring to the table is sufficiently overwhelming to make their adoption inevitable, and on this I think the answer is a clear no. As established above, LLMs just can't do top-flight work at all: at the heights of basically any discipline, we're still very much relying on unaugmented human work.
The clear flaw here is that cost isn't taken into account. A new technology needs to be better than the status quo at a given cost/price point.
Examples: mass produced textiles, photography, IKEA. Ostensibly not the highest quality, but the cheapest at a price point.
This was published today, I had to check the date to be sure. I used to be an applied researcher working in big tech and for the things I wanted to build if I had to pick between LLMs and hand picking a team of 100 from the best programmers / researchers in the world I would pick the LLMs. Of course the combination would be even better. I've had LLMs immediately understand concepts that took me months to effectively communicate to a colleague and there are some concepts I was unable to communicate to any other human at all. Then the LLMs could build what I needed in less time it would take me to set up a meeting about it.
> Any actor that's at all serious in their field is, sooner or later, going to hit a point where LLMs cease being useful to them and actively hinder their further progress, and we absolutely do not see the massively overwhelming advantages that LLMs would need to have in order to become inevitable.
I can only conclude from this that I am not at all serious in my field. That's okay. I'm too busy enjoying myself.
If you don’t use AI to scan for security bugs yourself, someone else will likely be using AI to find them first. So in that way, at least, LLMs could be considered inevitable.
The first part of the article is a thoughtful framework. The conclusion that LLMs are not inevitable because they aren't useful or that their utility can be substituted by humans is an extraordinarily flimsy claim.
I read "The level of social opprobrium directed at LLM use and at people attempting to pass off generated slop as work is immense" and immediately checked for the author's Bluesky link. This person is living in a bubble. Most people in tech are now using LLMs at work and there is no social opprobrium discouraging them.
The rest of the analysis seems to take it for granted that we have hit a wall and LLMs will improve no further. OK. We'll see how that prediction plays out.
> Most people in tech are now using LLMs at work and there is no social opprobrium discouraging them.
I don't know if "most people" is true, yet. I do think that the opprobrium has been silenced, and in corporate environments that has been systematic and top-down. Tokenmaxxing, leaderboards, monitoring: this is all part of making sure developers do not spend time considering the ethics, because the conclusions have been rendered moot.
"90% of professional developers were using AI coding agents at work at least weekly in one form or another (local agents or remote cloud agents), with 68% using them daily."
Re. context:
"The Developer Ecosystem and AI Pulse surveys are localized into eight languages: English, Spanish, Chinese, Japanese, Korean, German, French, and Portuguese. We apply quotas on the required number of responses by region to help achieve accurate global representation. ... The Developer Ecosystem Survey has been statistically reweighted to better represent the global developer population by region, employment status, programming language, and familiarity with JetBrains products"
We need to start talking about anti-AI psychosis. That people actually think their delusions fueled by these echo chambers are real is almost as worrying as the AI booster bubbles.
I'm gonna go ahead and make the prediction that this eventually morphs into a kind of religion, like flat earthers.
Nothing that AI will ever be valuable, everything AI does is steal, nothing it creates is new, everything that the big labs publishes is a scam or hype. Oh and "it's just doing X", where you can substitute "X" with some kind of surface level description of how the output layer in an LLM works.
These tenets are already pretty much formed, all it needs is to be formalized by some kind of name or manifesto similar to Q-anon, and we've arrived at a durable state of permanent denial.
There‘s hardly anything to talk about, since most of those anti-AI people use LLMs anyway. It‘s hypocrisy at best. If only that energy could be channeled in doing more about open-weight models-we need more AI-ownership, not less AI. That LLMs will somehow magically disappear should Anthropic or OpenAI go bust, is nothing but wishful thinking.
The author's absurd fantasy of how an LLM has to be used in order to fit their imagined adversary's idea of inevitable is absolute drivel. This article doesn't even build a straw man. It's just a pile of straw and manure.
Human intellectual effort is the tightrope walker in Thus Spoke Zarathustra; AI is the jester. LLMs can already solve programming and mathematical problems better and faster than humans. It's only a matter of time before other intellectual disciplines fall. We would be profoundly stupid not to embrace this change.
Empathy and big-picture thinking over myopic specialization will be the new moat.
One thing I've seen with LLMs that I've not seen with any other emergent technology is the level of backlash against it. I think we're seeing a point of polarization in society where there will be two truly opposing sides that are against each other and no reconciliation will be possible between them (pro and anti-AI), and that it has a good chance of fundamentally destabilizing society.
> I've not seen with any other emergent technology is the level of backlash against it.
i think those who had backlashes against machines and automation in the past would be similar tbh.
It's because when people feel, even if remotely, their livelihood going down the drain, they do anything and everything to fight it (even if it would be against the interest of overall progress - nobody wants to be the "sacrifice").
I mean, Luddites were hanged for murdering people. We're not quite there yet.
They were not just fighting for their livelihoods, though; the fight was at least as much about dignity and fair treatment.
And they were correct to do so: skilled workers who lost their work and ended up in industrial employment did not have better lives. It took a century to a century-and-a-half for industrial quality of life to get back to pre-industrial quality of life.
Loss of dignity is something that the AI industry is not considering as it renders entire swathes of the economy button-pushers for chatbots.
When loss of livelihood appears it will be too late and at too great a scale to fight back in the workplace; the fightback will be somewhere else.
I've seen a lot of people not wanting to learn to use a computer ("I prefer the old way") or not wanting to have a mobile phone ("I don't want to be reachable all the time") or a smartphone with touchscreen ("This feels like a too close interaction between the human and the device").
H.G Wells Time Machine has future society split into to: the childish consumer class and the driven engineering class, and the consumer class is the food of the engineering class. I could see this happening, with how cruel so many are, and trying to institutionalize that attitude.
I haven't seen much splitting into two groups of people who are for and against. It's more that individuals can see upsides - does cool stuff, and downsides - something like a rival lifeform that will be smarter than us.
I think that's a pretty odd framing, because the upsides are pretty relative and lopsided to those receiving certain benefits. The people who are anti-AI often are those who can acknowledge that AI does cool stuff, but that it's not worth it and doesn't provide any real benefit except by helping people keep up in a frenetic arms race to develop new tech.
Personally, I'm against AI but even if it could never be smarter than us and if it were at the state that it was last year, I'd still be against it due to the environmental cost.
I'm mildly pro but agree on the environmental costs. I think they should try to make it green energy only though not much chance with the current US admin. I'm not so enthused with current AI. I use last years like language translation a lot and I'm interested in the possible sci-fi future like curing diseases, some sort of immortality, abundance etc.
I keep seeing it and it's really bipolar. Boosters think it's the best thing ever and downplays all the issues while antis think it's completely useless and a disaster environmentally and morally.
Good luck saying LLMs are useful but still a net negative in the filter bubble this author is in. No, you also need to think it has zero utility or you're the enemy.
“That surveillance capitalism is a logic in action and not a technology is a vital point because surveillance capitalists want us to think that their practices are inevitable expressions of the technologies they employ. For example, in 2009 the public first became aware that Google maintains our search histories indefinitely: data that are available as raw-material supplies are also available to intelligence and law-enforcement agencies. When questioned about these practices, the corporation’s former CEO Eric Schmidt mused, ‘The reality is that search engines including Google do retain this information for some time.’
In truth, search engines do not retain, but surveillance capitalism does. Schmidt’s statement is a classic of misdirection that bewilders the public by conflating commercial imperatives and technological necessity.”
Shoshanna Zuboff, “The Age of Surveillance Capitalism”
It helps if the author does not confuse what LLMs actually do with the general misunderstanding that "LLMs do work". They do not "do work" and have never "done work", and this misunderstanding is all over tech.
What do LLMs to? You know this: they are sentence completion engines, that through this process of sentence completion can be used to create software than then "does work". This indirection is critical, it is "how this works" and is the true power of LLMs that is STILL not being recognized. The power of LLMs is their communications capacity, their ability to complete sentences, which is so subtle the entire world of software engineers and artificial intelligence everybody has not identified that simple "variable expansion" as the true power of LLMs. LLMs do not do work, they enable the creation of software that then does work.
With a technology so subtle, want to know what is inevitable? A bifurcation of the population into those that believe in magic and those that understand it well enough to make magic nobody considered possible. Why did I say "magic"? Because people are giving up understanding, and that makes what we do magic.
The fact that the author is using PowerBI as the example makes me think they are completely oblivious of the actual impact and utility LLMs have in other fields such as programming. Claiming it's useless and that anything it outputs is "markedly inferior to that of a human doing the same task" is an absurd basis to use for their argument.
I know it's a typo, but I wonder if "programmering" could be a useful new word for the act of creating programmers!
Oops, fixed but I think you're onto something!
It’s also just false. The good LLMs already produce output far better than the average programmer in most domains.
People like to talk about code as craft and art but the vast majority of the code that was written has always been mediocre at best. LLMs already beat it.
A focused experienced skilled programmer can do better but the market niche for that kind of code is actually small. Most commercial code just has to be good enough to accomplish a business need.
If you think of LLMs as statistically averaging machines and think of human programmer skill as a bell curve, it helps understand the different experiences with LLMs of different people. Those on the left hand side of the skill curve will see an uplift, those on the right hand side will experience degradation.
The more pertinent question in my mind is.. why does it still matter? Your customers don’t care about elegant code, they are about working products. There is some relation to good code and good customer experience e.g in terms of performance, but in general your customers won’t feel the impact from poor code. That assumes both pieces of code are functional though, and you do need to babysit LLMs to make sure it actually remains functional.
[delayed]
[dead]
There are LLM optimists and LLM pessimists.
The optimists have been more correct in predicting the capabilities and usefulness of LLMs.
The pessimists seem to have a hard time rationalizing what they thought with what’s actually happening.
I do feel that a lot of pessimists I hear keep banging away about hallucinations and untrustworthy outputs. It makes me think they’re willfully ignorant of the progress since they tried ChatGPT 3 several years ago and were underwhelmed.
I’m happy to engage in discourse on the impact and risks to environment, society, jobs, mental health, etc. There’s plenty of room for thoughtful exploration there.
The one thing I have no patience for is that LLMs produce nothing of value or have no technical worth.
People who understand computers and those who do not.
I have to keep reminding myself though, many of those pessimists are people “getting paid to not understand” as the saying goes.
It took 30 seconds with that Davinci model to predict where we are today, where we’ll be next year, and the eventual destruction if not outright extinction of humanity as we know it. Maybe the future is so grim many are simply in the denial stage still.
[dead]
"The first point is the question of whether an LLM can do work not markedly inferior to that of a human doing the same task or not. This one is debatable. An LLM absolutely cannot produce work to the highest human standards, or even a good human standard at the moment, and it's unlikely that it ever will."
This could have been fine maybe two years ago, but saying that in the era when LLMs are solving Millenium Prize Problems is incredibly obnoxious. All those opinionated "AI articles" feel like ragebait at this point.
GPT-4 felt like a slightly dim but still very useful intern.
GPT-6.1 (and Opus 5.5, etc.,) is a solid mid-career pro who can produce outputs very much on par with "good human standards" -- and, in some cases, far better than that.
Whatever in-house dev model they're using at OAI/Anthropic is, by all accounts, legitimately superhuman and capable of solving outstanding technical and mathematical problems with three hours of "Pro thinking."
OP's complaint is foolish, it reads like somebody who has never even used these things and has no idea what their capabilities actually are.
> who can produce outputs very much on par with "good human standards"
“Can produce”. Is doing a lot of heavy lifting there. It can, but then they also regularly write truly bafflingly bad code that no decent experienced dev would ever produce.
I’ll give you a few examples from last week. I had claude whip up a Kafka consumer. After a lot of back and forth I was pretty confident it worked and then I decided to dig into the code. I spotted some real head scratchers.
When starting up the consumer it wanted to pass a specific rebalance strategy, but then it realized that the library it was using didn’t support that strategy, so it needed to use the default.
Instead of just deleting the config option (and maybe leaving a comment), it created a function that removed that key from the map and used it like:
Then I started looking at the tests. They looked good but then I realized it wanted to be able to test without Kafka so what it had done was make multiple public functions that were mostly duplicates the real functions except that they didn’t call the Kafka library. Then it just tested those instead.Another frontier model reviewer was supposed to prevent that kind of thing but it didn’t catch it either.
I had 10 public functions that were only called in tests throughout the whole project. Essentially the tests were useless because they weren’t actually testing anything.
Clearly current frontier models are useful. And maybe they produce code that is better than the median dev by many metrics. But I don’t think they are anywhere near consistently producing better quality than a say a 70the percentile dev with 10 years experience.
And even when the quality is better than the median dev, I’m finding that the bugs are not the kind of thing that humans or LLMs are good at spotting.
I don't doubt it can, sometimes, produce output far better than most human can. The problem is: what happens what it don't ...
It's likely similar to what happens when the humans don't.
> An LLM absolutely cannot produce work to the highest human standards
yep. This is the choice quote.
Even most humans cannot produce work to the highest human standards. The fact is, most work does not need to be done to the highest human standards, it simply needs to be done to the lowest possible standard that someone would pay for, at the cheapest price.
The consumer chooses the cheapest price. Look at sweat shops, look at chinese manufacturing, look at offshoring. All of these produces an inferior product, and yet they are what gets the most profit and overwhelmingly the largest market share of consumer purchases.
You:
TFA: I'd recommend that you take 15->30 minutes and read the entire essay. It's a good read.It's so tiresome. I'm going to stop getting into these threads altogether soon. There's nothing to discuss with the ones who treat it like a religious belief. I keep thinking that they'll just try some of the tools and see reason, but you can't rationalize with the irrational.
I wish people who felt this way would just go use the tools they hate so much before passing judgement. I think many of them used it once, in a much worse form, many years ago and not since. Judging these things by the standards of 3 months ago is unfair, let alone the standards of 3 years ago.
The reality is that even if they used the tools, they still wouldn't change their mind.
Many people have incredible ability to ignore evidence.
> The technology can, in volume of adequate output or in quality of output, overwhelmingly outclass what alternative technologies can do. A moderate improvement isn't really enough to force inevitability: it has to be a massive difference.
> Now we come to the question of whether or not the difference that LLMs bring to the table is sufficiently overwhelming to make their adoption inevitable, and on this I think the answer is a clear no. As established above, LLMs just can't do top-flight work at all: at the heights of basically any discipline, we're still very much relying on unaugmented human work.
The clear flaw here is that cost isn't taken into account. A new technology needs to be better than the status quo at a given cost/price point.
Examples: mass produced textiles, photography, IKEA. Ostensibly not the highest quality, but the cheapest at a price point.
This was published today, I had to check the date to be sure. I used to be an applied researcher working in big tech and for the things I wanted to build if I had to pick between LLMs and hand picking a team of 100 from the best programmers / researchers in the world I would pick the LLMs. Of course the combination would be even better. I've had LLMs immediately understand concepts that took me months to effectively communicate to a colleague and there are some concepts I was unable to communicate to any other human at all. Then the LLMs could build what I needed in less time it would take me to set up a meeting about it.
> Any actor that's at all serious in their field is, sooner or later, going to hit a point where LLMs cease being useful to them and actively hinder their further progress, and we absolutely do not see the massively overwhelming advantages that LLMs would need to have in order to become inevitable.
I can only conclude from this that I am not at all serious in my field. That's okay. I'm too busy enjoying myself.
If you don’t use AI to scan for security bugs yourself, someone else will likely be using AI to find them first. So in that way, at least, LLMs could be considered inevitable.
Ironically, this might be the first time I wished an article was written by AI.
[flagged]
The first part of the article is a thoughtful framework. The conclusion that LLMs are not inevitable because they aren't useful or that their utility can be substituted by humans is an extraordinarily flimsy claim.
I read "The level of social opprobrium directed at LLM use and at people attempting to pass off generated slop as work is immense" and immediately checked for the author's Bluesky link. This person is living in a bubble. Most people in tech are now using LLMs at work and there is no social opprobrium discouraging them.
The rest of the analysis seems to take it for granted that we have hit a wall and LLMs will improve no further. OK. We'll see how that prediction plays out.
> Most people in tech are now using LLMs at work and there is no social opprobrium discouraging them.
I don't know if "most people" is true, yet. I do think that the opprobrium has been silenced, and in corporate environments that has been systematic and top-down. Tokenmaxxing, leaderboards, monitoring: this is all part of making sure developers do not spend time considering the ethics, because the conclusions have been rendered moot.
Something like 90% of devs are using LLMs. It's how software gets written now, end of story.
> Something like 90% of devs are using LLMs.
That needs a citation, and context. Globally? The USA? The Valley? Where is this number from?
JetBrains developer survey 2026:
https://blog.jetbrains.com/research/2026/08/ai-coding-agent-...
"90% of professional developers were using AI coding agents at work at least weekly in one form or another (local agents or remote cloud agents), with 68% using them daily."
Re. context:
"The Developer Ecosystem and AI Pulse surveys are localized into eight languages: English, Spanish, Chinese, Japanese, Korean, German, French, and Portuguese. We apply quotas on the required number of responses by region to help achieve accurate global representation. ... The Developer Ecosystem Survey has been statistically reweighted to better represent the global developer population by region, employment status, programming language, and familiarity with JetBrains products"
We need to start talking about anti-AI psychosis. That people actually think their delusions fueled by these echo chambers are real is almost as worrying as the AI booster bubbles.
I'm gonna go ahead and make the prediction that this eventually morphs into a kind of religion, like flat earthers.
Nothing that AI will ever be valuable, everything AI does is steal, nothing it creates is new, everything that the big labs publishes is a scam or hype. Oh and "it's just doing X", where you can substitute "X" with some kind of surface level description of how the output layer in an LLM works.
These tenets are already pretty much formed, all it needs is to be formalized by some kind of name or manifesto similar to Q-anon, and we've arrived at a durable state of permanent denial.
There‘s hardly anything to talk about, since most of those anti-AI people use LLMs anyway. It‘s hypocrisy at best. If only that energy could be channeled in doing more about open-weight models-we need more AI-ownership, not less AI. That LLMs will somehow magically disappear should Anthropic or OpenAI go bust, is nothing but wishful thinking.
They need a holy text.
Maybe an Orange Catholic Bible.
The author's absurd fantasy of how an LLM has to be used in order to fit their imagined adversary's idea of inevitable is absolute drivel. This article doesn't even build a straw man. It's just a pile of straw and manure.
Human intellectual effort is the tightrope walker in Thus Spoke Zarathustra; AI is the jester. LLMs can already solve programming and mathematical problems better and faster than humans. It's only a matter of time before other intellectual disciplines fall. We would be profoundly stupid not to embrace this change.
Empathy and big-picture thinking over myopic specialization will be the new moat.
One thing I've seen with LLMs that I've not seen with any other emergent technology is the level of backlash against it. I think we're seeing a point of polarization in society where there will be two truly opposing sides that are against each other and no reconciliation will be possible between them (pro and anti-AI), and that it has a good chance of fundamentally destabilizing society.
> I've not seen with any other emergent technology is the level of backlash against it.
i think those who had backlashes against machines and automation in the past would be similar tbh.
It's because when people feel, even if remotely, their livelihood going down the drain, they do anything and everything to fight it (even if it would be against the interest of overall progress - nobody wants to be the "sacrifice").
I mean, Luddites were hanged for murdering people. We're not quite there yet.
They were not just fighting for their livelihoods, though; the fight was at least as much about dignity and fair treatment.
And they were correct to do so: skilled workers who lost their work and ended up in industrial employment did not have better lives. It took a century to a century-and-a-half for industrial quality of life to get back to pre-industrial quality of life.
Loss of dignity is something that the AI industry is not considering as it renders entire swathes of the economy button-pushers for chatbots.
When loss of livelihood appears it will be too late and at too great a scale to fight back in the workplace; the fightback will be somewhere else.
I've seen a lot of people not wanting to learn to use a computer ("I prefer the old way") or not wanting to have a mobile phone ("I don't want to be reachable all the time") or a smartphone with touchscreen ("This feels like a too close interaction between the human and the device").
H.G Wells Time Machine has future society split into to: the childish consumer class and the driven engineering class, and the consumer class is the food of the engineering class. I could see this happening, with how cruel so many are, and trying to institutionalize that attitude.
Silicon Valley tech workers are not the subterranean Munrungs. They are the surface-dwelling Eloi. They just don't know it yet.
It's not a normal technology.
I haven't seen much splitting into two groups of people who are for and against. It's more that individuals can see upsides - does cool stuff, and downsides - something like a rival lifeform that will be smarter than us.
I think that's a pretty odd framing, because the upsides are pretty relative and lopsided to those receiving certain benefits. The people who are anti-AI often are those who can acknowledge that AI does cool stuff, but that it's not worth it and doesn't provide any real benefit except by helping people keep up in a frenetic arms race to develop new tech.
Personally, I'm against AI but even if it could never be smarter than us and if it were at the state that it was last year, I'd still be against it due to the environmental cost.
I'm mildly pro but agree on the environmental costs. I think they should try to make it green energy only though not much chance with the current US admin. I'm not so enthused with current AI. I use last years like language translation a lot and I'm interested in the possible sci-fi future like curing diseases, some sort of immortality, abundance etc.
I keep seeing it and it's really bipolar. Boosters think it's the best thing ever and downplays all the issues while antis think it's completely useless and a disaster environmentally and morally.
Good luck saying LLMs are useful but still a net negative in the filter bubble this author is in. No, you also need to think it has zero utility or you're the enemy.
You missed Gnome v KDE
“That surveillance capitalism is a logic in action and not a technology is a vital point because surveillance capitalists want us to think that their practices are inevitable expressions of the technologies they employ. For example, in 2009 the public first became aware that Google maintains our search histories indefinitely: data that are available as raw-material supplies are also available to intelligence and law-enforcement agencies. When questioned about these practices, the corporation’s former CEO Eric Schmidt mused, ‘The reality is that search engines including Google do retain this information for some time.’ In truth, search engines do not retain, but surveillance capitalism does. Schmidt’s statement is a classic of misdirection that bewilders the public by conflating commercial imperatives and technological necessity.”
Shoshanna Zuboff, “The Age of Surveillance Capitalism”
Cope.
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It helps if the author does not confuse what LLMs actually do with the general misunderstanding that "LLMs do work". They do not "do work" and have never "done work", and this misunderstanding is all over tech.
What do LLMs to? You know this: they are sentence completion engines, that through this process of sentence completion can be used to create software than then "does work". This indirection is critical, it is "how this works" and is the true power of LLMs that is STILL not being recognized. The power of LLMs is their communications capacity, their ability to complete sentences, which is so subtle the entire world of software engineers and artificial intelligence everybody has not identified that simple "variable expansion" as the true power of LLMs. LLMs do not do work, they enable the creation of software that then does work.
With a technology so subtle, want to know what is inevitable? A bifurcation of the population into those that believe in magic and those that understand it well enough to make magic nobody considered possible. Why did I say "magic"? Because people are giving up understanding, and that makes what we do magic.