14 ms·

Just to be clear, the article is NOT criticizing this. To the contrary, it's presenting it as expected, thanks to Solow's productivity paradox [1]. Which is th

Just to be clear, the article is NOT criticizing this. To the contrary, it's presenting it as expected, thanks to Solow's productivity paradox [1]. Which is that information technology similarly (and seemingly shockingly) didn't produce any net economic gains in the 1970's or 1980's despite all the computerization. It wasn't until the mid-to-late 1990's that information technology finally started to show clear benefit to the economy overall. The reason is that investing in IT was very expensive, there were lots of wasted efforts, and it took a long time for the benefits to outweigh the costs across the entire economy. And so we should expect AI to look the same -- it's helping lots of people, but it's also costing an extraordinary amount of money, and the few people it's helping is currently at least outweighed by the people wasting time with it and its expense. But, we should recognize that it's very early days, and that productivity will rise with time, and costs will come down, as we learn to integrate it with best practices. [1] https://en.wikipedia.org/wiki/Productivity_paradox https://en.wikipedia.org/wiki/Productivity_paradox

kamaal 8mo ago
One part of the system moving fast doesn't change the speed of the system all that much. The thing to note is, verifying if something got done is harder and takes time in the same ballpark as doing the work. If people are serious about AI productivity, lets start by addressing how we can verify program correctness quickly. Everything else is just a Ferrari between two traffic red lights.
- hawaiianbrah 8mo ago
  Really? I disagree that verifying is as hard as doing the work yourself. It’s like P != NP.
torben-friis 8mo ago
The comparison seems flawed in terms of cost. A Claude subscription is 20 bucks per worker if using personal accounts billed to the company, which is not very far from common office tools like slack. Onboarding a worker to Claude or ChatGPT is ridiculously easy compared to teaching a 1970’s manual office worker to use an early computer. Larger implementations like automating customer service might be more costly, but I think there are enough short term supposed benefits that something should be showing there.
- meager_wikis 8mo ago
  If anything, the 'scariness' of an old computer probably protected the company in many ways. AI's approachability to the average office worker, specifically how it makes it seem like it easy to deploy/run/triage enterprise software, will continue to pwn.
- gruez 8mo ago
  How viable are the $20/month subscriptions for actual work and are they loss making for Anthropic? I've heard both of people needing to get higher tiers to get anything done in Claude Code and also that the subscriptions are (heavily?) subsidized by Anthropic, so the "just another $20 SaaS" argument doesn't sound too good.
  - 8note 8mo ago
    id guess the 200 subscription sufficient per person. but at that point you could go for a bugger one and split amongst headcount
  - simonw 8mo ago
    I am confident that Anthropic make revenue from that $20 than the electricity and server costs needed to serve that customer. Claude Code has rate limits for a reason: I expect they are carefully designed to ensure that the average user doesn't end up losing Anthropic money, and that even extreme heavy users don't cause big enough losses for it to be a problem. Everything I've heard makes me believe the margins on inference are quite high. The AI labs lose money because of the R&D and training costs, not because they're giving electricity and server operational costs away for free.
    - Esophagus4 8mo ago
      I always assumed that with inference being so cheap, my subscription fees were paying for training costs, not inference.
      - smashed 8mo ago
lawstkawz 8mo ago
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calvinmorrison 8mo ago
> it's helping lots of people, but it's also costing an extraordinary amount of money Is it fair to say that wall street is betting America's collective pensions on AI...
- HWR_14 8mo ago
  Very few people have pensions anymore. People now direct their own retirement funds.
  - noddingham 8mo ago
    That's what he was saying. Wall Street (the stock market) are people's "pensions" now because everyone has a 401k or equivalent so their retirement is tied to the market. Thus, these companies are betting America's collective retirement on AI...
    - HWR_14 8mo ago
      I thought he was talking about actual pension funds, which still exist and invest large sums of money in Wall Street. But make sure your 401k doesn't include AI funds then. You should have a choice over what part of the market to invest in.
- autoexec 8mo ago
  They're betting a lot more than that, but since all their chips are externalities they don't care.
_aavaa_ 8mo ago
For more on this exact topic and an answer to Solow’s Paradox, see, the excellent, The Dynamo and the Computer by Paul David [0]. [0]: https://www.almendron.com/tribuna/wp-content/uploads/2018/03/the-dynamo-and-the-computer-an-historical-perspective-on-the-modern-productivity-paradox.pdf https://www.almendron.com/tribuna/wp-content/uploads/2018/03...
- gsf_emergency_6 8mo ago
  Stanford prof rebutts David's idea[0] that it's difficult to extract productivity from the data https://www.nber.org/system/files/working_papers/w25148/w25148.pdf https://www.nber.org/system/files/working_papers/w25148/w251... I don't agree that real GDP measures what he thinks it measures, but he opines >Data released this week offers a striking corrective to the narrative that AI has yet to have an impact on the US economy as a whole. While initial reports suggested a year of steady labour expansion in the US, the new figures reveal that total payroll growth was revised downward by approximately 403,000 jobs. Crucially, this downward revision occurred while real GDP remained robust, including a 3.7 per cent growth rate in the fourth quarter. This decoupling — maintaining high output with significantly lower labour input — is the hallmark of productivity growth. https://www.ft.com/content/4b51d0b4-bbfe-4f05-b50a-1d485d419dc5 https://www.ft.com/content/4b51d0b4-bbfe-4f05-b50a-1d485d419... [0] on the basis that IT and AI are not general technologies in the mold of the dynamo, keyword "intangibles", see section 4 p21, A method to measure intangibles
  - PowerElectronix 8mo ago
    GDP growth measurements have a big bias due to tariffs on, tariffs off, tariffs on again policies wrecking imports and exports numbers. Consumer spending is up, too, so I too fail to see that gdp growth while jobs are not as up as expected is due to AI making us more productive and not just people spending more after months of increased savings due to tariffs.
    - reg_dunlop 8mo ago
      I'm curious how "consumer spending" is quantified here. Is consumer spending measured in total dollars spent? If so, isn't that curious wrinkle in an economy of rising prices, and decreasing purchasing power? If true, I believe less quantity could be purchased at a higher cost per person, making it appear that consumer spending is up. Presumably these numbers are benchmarked/peg to some sort of constant and/or standardization
ozgrakkurt 8mo ago
I don’t think LLMs are similar to computers in terms of productivity boost
gsf_emergency_6 8mo ago
Fwiw fortune had another article this week saying this J-curve of "General Technology" is showing up in the latest BLS data https://fortune.com/2026/02/15/ai-productivity-liftoff-doubling-2025-jobs-report-transition-harvest-phase-j-curve/ https://fortune.com/2026/02/15/ai-productivity-liftoff-doubl... Source of the Stanford-approved opinion: https://www.ft.com/content/4b51d0b4-bbfe-4f05-b50a-1d485d419dc5 https://www.ft.com/content/4b51d0b4-bbfe-4f05-b50a-1d485d419... https://www.apolloacademy.com/waiting-for-the-ai-j-curve/ https://www.apolloacademy.com/waiting-for-the-ai-j-curve/
joering2 8mo ago
> And so we should expect AI to look the same Is that somewhat substantiated assumption? I recall learning on University in 2001 the history of AI and that initial frameworks were written in 70's and that prediction was we will reach human-like intelligence by 2000. Just because Sama came up with this somewhat breakthrough of an AI, it doesn't mean that equal improvement leaps will be done on a monthly/annual basis going forward. We may as well not make another huge leaps or reach what some say human intelligence level in 10 years or so.
killingtime74 8mo ago
productivity may rise with time, and costs may come down. The money is already spent
- johnnienaked 8mo ago
  Some of the money is spent. What happens when better models, more efficient cooling techniques, and other technologies hit? Seems like the best strategy at this point isn't dumping your entire FCF into datacenters, but wait and see if there's even a viable business efficiency improvement first.
heresie-dabord 8mo ago
> It wasn't until the mid-to-late 1990's that information technology finally started to show clear benefit to the economy overall. The 1990s boom was in large part due to connectivity -- millions[1] of computers joined the Internet. [1] _ In the 1990s. Today, there are billions of devices connected, most of them Android devices.
- ericfr11 8mo ago
  Android in the 90s Not really
whynotminot 8mo ago
It’s also pretty wild to me how people still don’t really even know how to use it. On hacker news, a very tech literate place, I see people thinking modern AI models can’t generate working code. The other day in real life I was talking to a friend of mine about ChatGPT. They didn’t know you needed to turn on “thinking” to get higher quality results. This is a technical person who has worked at Amazon. You can’t expect revolutionary impact while people are still learning how to even use the thing. We’re so early.
- politelemon 8mo ago
  You are assuming that we all work on the same tasks and should have exactly the same experience with it, which is it course far from the truth. It's probably best to start with that base assumption and work on the implications from there. As for the last example, for all the money being spent on this area, if someone is expected to perform a workflow based on the kind of question they're supposed to ask, that's a failure in the packaging and discoverability aspect of the product, the leaky abstraction only helps some of us who know why it's there.
- harrall 8mo ago
  I’ve been helping normal people at work use AI and there’s two groups that are really struggling: 1. People who only think of using AI in very specific scenarios. They don’t know when you use it outside of the obvious “to write code” situations and they don’t really use AI effectively and get deflated when AI outputs the occasional garbage. They think “isn’t AI supposed to be good at writing code?” 2. People who let AI do all the thinking. Sometimes they’ll use AI to do everything and you have to tell them to throw it all away because it makes no sense. These people also tend to dump analyses straight from AI into Slack because they lack the tools to verify if a given analysis is correct. To be honest, I help them by teaching them fairly rigid workflows like “you can use AI if you are in this specific situation.” I think most people will only pick up tools effectively if there is a clear template. It’s basically on-the-job training.
- tstrimple 8mo ago
  > On hacker news, a very tech literate place I think this is the prior you should investigate. That may be what HN used to be. But it's been a long time since it has been an active reality. You can still see actual expert opinions on HN, but they are the minority more and more.
Waterluvian 8mo ago
Wow I didn’t realize that. But I always thought it. I was bewildered that anyone got any real value out of any of that pre-VisiCalc (or even VisiCalc) computer tech for business. It all looked kinda clumsy.
- KellyCriterion 8mo ago
  (pre) VisiCalc: You have to understand that the primary users (accountants etc.) do not care about how a thing looks in their working process: If a tool helps them, they will use it even if its ugly according to aesthetical frontend questions :-) (Think about this old black/white or green mainframe screens - horrible looking but it gets their job done)
overgard 8mo ago
The coding tools are not hard to pick up. Agent chat and autocomplete in IDE's are braindead simple, and even TUI's like Claude are extremely easy to pickup (I think it took me a day?) And despite what the vibers like to pretend, learning to prompt them isn't that hard either. Or, let me clarify, if you know how to code, and you know how you want something coded, prompting them isn't that hard. I can't imagine it'll take that long for an impact to be seen, if there is a major impact to be seen. I think it's more likely that people "feel" more productive, and/or we're measuring bad things (lines of code is an awful way to measure productivity -- especially considering that these agents duplicate code all the time so bloat is a given unless you actively work to recombine things and create new abstractions)
- kylebyte 8mo ago
  It reminds me a lot of adderall's effect on people without ADHD. A pretty universal feeling that it's making you smarter, paired with no measurable increase in test scores.
  - overgard 8mo ago
    That's a good analogy. I've never done stimulants, but from what I've heard about them they make people very active but that isn't the same as productive.
masteruvpuppetz 8mo ago
An old office colleague used to tell us there was a time when he'd print a report prepared with Lotus123 (Ancient Excel) and their boss would verify the calculations on a calculator saying computers are not reliable. :o
__jf__ 8mo ago
Paul Strassmann wrote a book in 1990 called "Business Value of Computers" that showed that it matters where money on computers is spent. Only firms that spent it on their core business processes showed increased revenues whereas the ones that spent it on peripheral business processes didn't.
- Underqualified 8mo ago
  This is my feeling about both IT and AI. It enables companies to do a lot of things which don't really bring value. One of the biggest use case for AI in the company I work for now is powerBI report generation. Fine, but a couple of years ago we didn't even have all these graphs and reports. I'm not sure they bring actual value, since I see decisions still being made mostly on intuition.
globular-toast 8mo ago
If things like computer-aided design and improved supply chain management, for example, make manufactured goods last longer and cause less waste, I would expect IT to cause productivity to go down. I drive a 15 year old car and use a 12 year old PC. It's a good thing that productivity goes down, or stays the same.
arisAlexis 8mo ago
Only it's much more exponential
kittbuilds 8mo ago
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unkulunkulu 8mo ago
Ok, this article inspired some positivity in my view. Here comes, of course a disclaimer that this is just "wishful thinking", but still. So we are in the process of "adapting a technology". Welcome, keep calm, observe, don't be ashamed to feel emotions like fear, excitement, anger and all else. While adapting, we learn how to use it better and better. At first, we try "do all the work for me", then "ok, that was bad, plan what you would do, good, adjust, ok do it like this" etc etc. A couple of years into the future this knowledge is just "passed on". If productivity grew and we "figured out how to get more out of the universe", then no jobs had to be lost, just readapted. And "investors" get happy not by "replacing workers", but by "reaping win-win rewards" from the universe at large. There are dangers of course, like "maybe this is truly a huge win-win, but some loses can be hidden, like ecology", but "I hope there are people really addressing these problems and this win-win will help them be more productive as well".
matsemann 8mo ago
Is this like the hotels first jumping on the wifi bandwagon? Spent lots of money up front for expensive tech. Years later, anyone could buy a cheap router and set up, so every hotel had wifi. But the original high-end hotels that were first out with wifi and paid much for it, has the worst and old wifi and charge users for it, still trying to recoup the costs.
TimByte 8mo ago
Yet with IT, the bottleneck was largely technical and capital-related, whereas with AI it feels more organizational and cognitive
pragmatic 8mo ago
You’re missing the true value, the network. Wide spread internet access turned expensive toys (PCs) into useful assets.
JMKH42 8mo ago
>And so we should expect AI to look the same - Maybe! Or it might never pan out, or it may pan out way better. Complicated things like this rarely turn out the way people expect, no matter how smart.
- bunderbunder 8mo ago
  I’m thinking survivorship bias here. “Information Technology” is such a wide term, and we immediately think of the IT we currently use. Many of us can’t even remember all the blind alleys we wasted resources on in the ‘80s, especially those of us who weren’t there. I count myself among that group because I was a kid and didn’t pay much attention to business. But I can say that, judging by historical artifacts, a lot of it was along the same broad lines as AI. And we maybe don’t realize how serious people were about it back then. The technology that actually changed the world was so comparatively boring and pragmatic that the stuff that was being hyped back then seems comically overwrought. It’s easy to assume it must have been a joke all along.
bitgeist 8mo ago
I like your username.
deleted 8mo ago
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nz 8mo ago
I mean the productivity paradox was only temporarily remedied. Around 2005 we entered a second version of the paradox and it persists to this day. I'll note that 2005 was when the internet became dominated by walled-gardens and social-media, _and_ it was the last year that people got to use the internet without smartphones (in 2006 LG released a smartphone, with Apple releasing iPhone in 2007). The combination of attention-draining social media walled gardens, and the high performance pocket-computers (which are really designed for consumption instead of productivity), created a positive feedback loop that helped destroy the productivity that we won by defeating the paradox in the 1990s. And we have been struggling against this new paradox for twenty years, since. AI seems like it should defeat the paradox because it is a kind of hands-free system, perfect for mobile phones -- but this is really just a very expensive solution to a problem that we have created and allowed to fester. We could just shun the walled gardens, and demand to be paid for our attention and data. The new productivity paradox (which I do not think AI in its current form can fix[1][2]), is the price that we pay for a prosperous and valuable advertising industry. And as long as the web is seen as an ad-channel, and as long as the web is always vibrating in your pocket, we will keep paying this price. We will eventually end up (metaphorically) lobotomizing our children, and families, and communities, so that the grand-children of ad-executives and tech-bros and frat-bros can grow up healthy, psychologically stable, educated, and comfortably wealthy. (Brain drain: now available literally everywhere). [1]: It is telling that most LLMs are centralized, and are most useful as search-engines/information-retrieval-systems. The centralization makes them _spyware_, and their ability to directly answer any question, encourages users to actually ask direct questions, instead of stringing search-terms together. This makes the prompts high-signal advertising data (i.e. instead inferring what you are looking for from the search-string, these companies can see _exactly_ what you are looking for and why -- and with LLMs, they can probably turn these promps into joint-probability-tables or whatever other kind of serialization they need to figure out which products to sell you (either on the web or directly in the response to your prompt)). [2]: As far as copyright infringement goes, LLM outputs may require mass clean-room rewrites (so your productivity, as pathetic as it already is, now gets _halved_ long term) of text, prose, code, and anything else that is produced with them, because of how copyright law works. In legal arts this is called _the fruit of the poison tree_, and any short-term productivity gains, may become long term liabilities that need to be replaced due to _legal mandate_ -- so even if LLMs can eventually produce perfect and faultless outputs, the copyright laws _in all 200+ countries_ would have to be torn down and rebuilt (and this will certainly come at great expense).
dang 8mo ago
Thanks! we've swapped the baity title with that phrase above.

kamaal 8mo ago

One part of the system moving fast doesn't change the speed of the system all that much. The thing to note is, verifying if something got done is harder and takes time in the same ballpark as doing the work. If people are serious about AI productivity, lets start by addressing how we can verify program correctness quickly. Everything else is just a Ferrari between two traffic red lights.

hawaiianbrah 8mo ago
Really? I disagree that verifying is as hard as doing the work yourself. It’s like P != NP.

torben-friis 8mo ago

The comparison seems flawed in terms of cost. A Claude subscription is 20 bucks per worker if using personal accounts billed to the company, which is not very far from common office tools like slack. Onboarding a worker to Claude or ChatGPT is ridiculously easy compared to teaching a 1970’s manual office worker to use an early computer. Larger implementations like automating customer service might be more costly, but I think there are enough short term supposed benefits that something should be showing there.

meager_wikis 8mo ago
If anything, the 'scariness' of an old computer probably protected the company in many ways. AI's approachability to the average office worker, specifically how it makes it seem like it easy to deploy/run/triage enterprise software, will continue to pwn.
gruez 8mo ago
How viable are the $20/month subscriptions for actual work and are they loss making for Anthropic? I've heard both of people needing to get higher tiers to get anything done in Claude Code and also that the subscriptions are (heavily?) subsidized by Anthropic, so the "just another $20 SaaS" argument doesn't sound too good.
- 8note 8mo ago
  id guess the 200 subscription sufficient per person. but at that point you could go for a bugger one and split amongst headcount
- simonw 8mo ago
  I am confident that Anthropic make revenue from that $20 than the electricity and server costs needed to serve that customer. Claude Code has rate limits for a reason: I expect they are carefully designed to ensure that the average user doesn't end up losing Anthropic money, and that even extreme heavy users don't cause big enough losses for it to be a problem. Everything I've heard makes me believe the margins on inference are quite high. The AI labs lose money because of the R&D and training costs, not because they're giving electricity and server operational costs away for free.
  - Esophagus4 8mo ago
    I always assumed that with inference being so cheap, my subscription fees were paying for training costs, not inference.
    - smashed 8mo ago

lawstkawz 8mo ago

[dead]

calvinmorrison 8mo ago

> it's helping lots of people, but it's also costing an extraordinary amount of money Is it fair to say that wall street is betting America's collective pensions on AI...

HWR_14 8mo ago
Very few people have pensions anymore. People now direct their own retirement funds.
- noddingham 8mo ago
  That's what he was saying. Wall Street (the stock market) are people's "pensions" now because everyone has a 401k or equivalent so their retirement is tied to the market. Thus, these companies are betting America's collective retirement on AI...
  - HWR_14 8mo ago
    I thought he was talking about actual pension funds, which still exist and invest large sums of money in Wall Street. But make sure your 401k doesn't include AI funds then. You should have a choice over what part of the market to invest in.
autoexec 8mo ago
They're betting a lot more than that, but since all their chips are externalities they don't care.

_aavaa_ 8mo ago

For more on this exact topic and an answer to Solow’s Paradox, see, the excellent, The Dynamo and the Computer by Paul David [0]. [0]: https://www.almendron.com/tribuna/wp-content/uploads/2018/03/the-dynamo-and-the-computer-an-historical-perspective-on-the-modern-productivity-paradox.pdf https://www.almendron.com/tribuna/wp-content/uploads/2018/03...

gsf_emergency_6 8mo ago
Stanford prof rebutts David's idea[0] that it's difficult to extract productivity from the data https://www.nber.org/system/files/working_papers/w25148/w25148.pdf https://www.nber.org/system/files/working_papers/w25148/w251... I don't agree that real GDP measures what he thinks it measures, but he opines >Data released this week offers a striking corrective to the narrative that AI has yet to have an impact on the US economy as a whole. While initial reports suggested a year of steady labour expansion in the US, the new figures reveal that total payroll growth was revised downward by approximately 403,000 jobs. Crucially, this downward revision occurred while real GDP remained robust, including a 3.7 per cent growth rate in the fourth quarter. This decoupling — maintaining high output with significantly lower labour input — is the hallmark of productivity growth. https://www.ft.com/content/4b51d0b4-bbfe-4f05-b50a-1d485d419dc5 https://www.ft.com/content/4b51d0b4-bbfe-4f05-b50a-1d485d419... [0] on the basis that IT and AI are not general technologies in the mold of the dynamo, keyword "intangibles", see section 4 p21, A method to measure intangibles
- PowerElectronix 8mo ago
  GDP growth measurements have a big bias due to tariffs on, tariffs off, tariffs on again policies wrecking imports and exports numbers. Consumer spending is up, too, so I too fail to see that gdp growth while jobs are not as up as expected is due to AI making us more productive and not just people spending more after months of increased savings due to tariffs.
  - reg_dunlop 8mo ago
    I'm curious how "consumer spending" is quantified here. Is consumer spending measured in total dollars spent? If so, isn't that curious wrinkle in an economy of rising prices, and decreasing purchasing power? If true, I believe less quantity could be purchased at a higher cost per person, making it appear that consumer spending is up. Presumably these numbers are benchmarked/peg to some sort of constant and/or standardization

ozgrakkurt 8mo ago

I don’t think LLMs are similar to computers in terms of productivity boost

gsf_emergency_6 8mo ago

Fwiw fortune had another article this week saying this J-curve of "General Technology" is showing up in the latest BLS data https://fortune.com/2026/02/15/ai-productivity-liftoff-doubling-2025-jobs-report-transition-harvest-phase-j-curve/ https://fortune.com/2026/02/15/ai-productivity-liftoff-doubl... Source of the Stanford-approved opinion: https://www.ft.com/content/4b51d0b4-bbfe-4f05-b50a-1d485d419dc5 https://www.ft.com/content/4b51d0b4-bbfe-4f05-b50a-1d485d419... https://www.apolloacademy.com/waiting-for-the-ai-j-curve/ https://www.apolloacademy.com/waiting-for-the-ai-j-curve/

joering2 8mo ago

> And so we should expect AI to look the same Is that somewhat substantiated assumption? I recall learning on University in 2001 the history of AI and that initial frameworks were written in 70's and that prediction was we will reach human-like intelligence by 2000. Just because Sama came up with this somewhat breakthrough of an AI, it doesn't mean that equal improvement leaps will be done on a monthly/annual basis going forward. We may as well not make another huge leaps or reach what some say human intelligence level in 10 years or so.

killingtime74 8mo ago

productivity may rise with time, and costs may come down. The money is already spent

johnnienaked 8mo ago
Some of the money is spent. What happens when better models, more efficient cooling techniques, and other technologies hit? Seems like the best strategy at this point isn't dumping your entire FCF into datacenters, but wait and see if there's even a viable business efficiency improvement first.

heresie-dabord 8mo ago

> It wasn't until the mid-to-late 1990's that information technology finally started to show clear benefit to the economy overall. The 1990s boom was in large part due to connectivity -- millions[1] of computers joined the Internet. [1] _ In the 1990s. Today, there are billions of devices connected, most of them Android devices.

ericfr11 8mo ago
Android in the 90s Not really

whynotminot 8mo ago

It’s also pretty wild to me how people still don’t really even know how to use it. On hacker news, a very tech literate place, I see people thinking modern AI models can’t generate working code. The other day in real life I was talking to a friend of mine about ChatGPT. They didn’t know you needed to turn on “thinking” to get higher quality results. This is a technical person who has worked at Amazon. You can’t expect revolutionary impact while people are still learning how to even use the thing. We’re so early.

politelemon 8mo ago
You are assuming that we all work on the same tasks and should have exactly the same experience with it, which is it course far from the truth. It's probably best to start with that base assumption and work on the implications from there. As for the last example, for all the money being spent on this area, if someone is expected to perform a workflow based on the kind of question they're supposed to ask, that's a failure in the packaging and discoverability aspect of the product, the leaky abstraction only helps some of us who know why it's there.
harrall 8mo ago
I’ve been helping normal people at work use AI and there’s two groups that are really struggling: 1. People who only think of using AI in very specific scenarios. They don’t know when you use it outside of the obvious “to write code” situations and they don’t really use AI effectively and get deflated when AI outputs the occasional garbage. They think “isn’t AI supposed to be good at writing code?” 2. People who let AI do all the thinking. Sometimes they’ll use AI to do everything and you have to tell them to throw it all away because it makes no sense. These people also tend to dump analyses straight from AI into Slack because they lack the tools to verify if a given analysis is correct. To be honest, I help them by teaching them fairly rigid workflows like “you can use AI if you are in this specific situation.” I think most people will only pick up tools effectively if there is a clear template. It’s basically on-the-job training.
tstrimple 8mo ago
> On hacker news, a very tech literate place I think this is the prior you should investigate. That may be what HN used to be. But it's been a long time since it has been an active reality. You can still see actual expert opinions on HN, but they are the minority more and more.

Waterluvian 8mo ago

Wow I didn’t realize that. But I always thought it. I was bewildered that anyone got any real value out of any of that pre-VisiCalc (or even VisiCalc) computer tech for business. It all looked kinda clumsy.

KellyCriterion 8mo ago
(pre) VisiCalc: You have to understand that the primary users (accountants etc.) do not care about how a thing looks in their working process: If a tool helps them, they will use it even if its ugly according to aesthetical frontend questions :-) (Think about this old black/white or green mainframe screens - horrible looking but it gets their job done)

overgard 8mo ago

The coding tools are not hard to pick up. Agent chat and autocomplete in IDE's are braindead simple, and even TUI's like Claude are extremely easy to pickup (I think it took me a day?) And despite what the vibers like to pretend, learning to prompt them isn't that hard either. Or, let me clarify, if you know how to code, and you know how you want something coded, prompting them isn't that hard. I can't imagine it'll take that long for an impact to be seen, if there is a major impact to be seen. I think it's more likely that people "feel" more productive, and/or we're measuring bad things (lines of code is an awful way to measure productivity -- especially considering that these agents duplicate code all the time so bloat is a given unless you actively work to recombine things and create new abstractions)

kylebyte 8mo ago
It reminds me a lot of adderall's effect on people without ADHD. A pretty universal feeling that it's making you smarter, paired with no measurable increase in test scores.
- overgard 8mo ago
  That's a good analogy. I've never done stimulants, but from what I've heard about them they make people very active but that isn't the same as productive.

masteruvpuppetz 8mo ago

An old office colleague used to tell us there was a time when he'd print a report prepared with Lotus123 (Ancient Excel) and their boss would verify the calculations on a calculator saying computers are not reliable. :o

__jf__ 8mo ago

Paul Strassmann wrote a book in 1990 called "Business Value of Computers" that showed that it matters where money on computers is spent. Only firms that spent it on their core business processes showed increased revenues whereas the ones that spent it on peripheral business processes didn't.

Underqualified 8mo ago
This is my feeling about both IT and AI. It enables companies to do a lot of things which don't really bring value. One of the biggest use case for AI in the company I work for now is powerBI report generation. Fine, but a couple of years ago we didn't even have all these graphs and reports. I'm not sure they bring actual value, since I see decisions still being made mostly on intuition.

globular-toast 8mo ago

If things like computer-aided design and improved supply chain management, for example, make manufactured goods last longer and cause less waste, I would expect IT to cause productivity to go down. I drive a 15 year old car and use a 12 year old PC. It's a good thing that productivity goes down, or stays the same.

arisAlexis 8mo ago

Only it's much more exponential

kittbuilds 8mo ago

[dead]

unkulunkulu 8mo ago

Ok, this article inspired some positivity in my view. Here comes, of course a disclaimer that this is just "wishful thinking", but still. So we are in the process of "adapting a technology". Welcome, keep calm, observe, don't be ashamed to feel emotions like fear, excitement, anger and all else. While adapting, we learn how to use it better and better. At first, we try "do all the work for me", then "ok, that was bad, plan what you would do, good, adjust, ok do it like this" etc etc. A couple of years into the future this knowledge is just "passed on". If productivity grew and we "figured out how to get more out of the universe", then no jobs had to be lost, just readapted. And "investors" get happy not by "replacing workers", but by "reaping win-win rewards" from the universe at large. There are dangers of course, like "maybe this is truly a huge win-win, but some loses can be hidden, like ecology", but "I hope there are people really addressing these problems and this win-win will help them be more productive as well".

matsemann 8mo ago

Is this like the hotels first jumping on the wifi bandwagon? Spent lots of money up front for expensive tech. Years later, anyone could buy a cheap router and set up, so every hotel had wifi. But the original high-end hotels that were first out with wifi and paid much for it, has the worst and old wifi and charge users for it, still trying to recoup the costs.

TimByte 8mo ago

Yet with IT, the bottleneck was largely technical and capital-related, whereas with AI it feels more organizational and cognitive

pragmatic 8mo ago

You’re missing the true value, the network. Wide spread internet access turned expensive toys (PCs) into useful assets.

JMKH42 8mo ago

>And so we should expect AI to look the same - Maybe! Or it might never pan out, or it may pan out way better. Complicated things like this rarely turn out the way people expect, no matter how smart.

bunderbunder 8mo ago
I’m thinking survivorship bias here. “Information Technology” is such a wide term, and we immediately think of the IT we currently use. Many of us can’t even remember all the blind alleys we wasted resources on in the ‘80s, especially those of us who weren’t there. I count myself among that group because I was a kid and didn’t pay much attention to business. But I can say that, judging by historical artifacts, a lot of it was along the same broad lines as AI. And we maybe don’t realize how serious people were about it back then. The technology that actually changed the world was so comparatively boring and pragmatic that the stuff that was being hyped back then seems comically overwrought. It’s easy to assume it must have been a joke all along.

bitgeist 8mo ago

I like your username.

deleted 8mo ago

[deleted]

nz 8mo ago

I mean the productivity paradox was only temporarily remedied. Around 2005 we entered a second version of the paradox and it persists to this day. I'll note that 2005 was when the internet became dominated by walled-gardens and social-media, _and_ it was the last year that people got to use the internet without smartphones (in 2006 LG released a smartphone, with Apple releasing iPhone in 2007). The combination of attention-draining social media walled gardens, and the high performance pocket-computers (which are really designed for consumption instead of productivity), created a positive feedback loop that helped destroy the productivity that we won by defeating the paradox in the 1990s. And we have been struggling against this new paradox for twenty years, since. AI seems like it should defeat the paradox because it is a kind of hands-free system, perfect for mobile phones -- but this is really just a very expensive solution to a problem that we have created and allowed to fester. We could just shun the walled gardens, and demand to be paid for our attention and data. The new productivity paradox (which I do not think AI in its current form can fix[1][2]), is the price that we pay for a prosperous and valuable advertising industry. And as long as the web is seen as an ad-channel, and as long as the web is always vibrating in your pocket, we will keep paying this price. We will eventually end up (metaphorically) lobotomizing our children, and families, and communities, so that the grand-children of ad-executives and tech-bros and frat-bros can grow up healthy, psychologically stable, educated, and comfortably wealthy. (Brain drain: now available literally everywhere). [1]: It is telling that most LLMs are centralized, and are most useful as search-engines/information-retrieval-systems. The centralization makes them _spyware_, and their ability to directly answer any question, encourages users to actually ask direct questions, instead of stringing search-terms together. This makes the prompts high-signal advertising data (i.e. instead inferring what you are looking for from the search-string, these companies can see _exactly_ what you are looking for and why -- and with LLMs, they can probably turn these promps into joint-probability-tables or whatever other kind of serialization they need to figure out which products to sell you (either on the web or directly in the response to your prompt)). [2]: As far as copyright infringement goes, LLM outputs may require mass clean-room rewrites (so your productivity, as pathetic as it already is, now gets _halved_ long term) of text, prose, code, and anything else that is produced with them, because of how copyright law works. In legal arts this is called _the fruit of the poison tree_, and any short-term productivity gains, may become long term liabilities that need to be replaced due to _legal mandate_ -- so even if LLMs can eventually produce perfect and faultless outputs, the copyright laws _in all 200+ countries_ would have to be torn down and rebuilt (and this will certainly come at great expense).

dang 8mo ago

Thanks! we've swapped the baity title with that phrase above.