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AI adoption and Solow's productivity paradox

fortune.com

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Re: AI adoption and Solow's productivity paradox

#431

Post by IshKebab »

slopinthebag wrote: post #169
whynotminot wrote: post #143

Earlier quoted context omitted.

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 expec…

> I see people thinking modern AI models can’t generate working code. Really? Can you show any examples of someone claiming AI models cannot generate working code? I haven't seen anyone make that claim in years, even from the most skeptical critics.

I'll claim it. They can't generate working code for the things I am working on. They seem to be too complex or in languages that are too niche.

They can do a tolerable job with super popular /simple things like web dev and Python. It really depends on what you're doing.

Re: AI adoption and Solow's productivity paradox

#432

Post by lonelyasacloud »

flurdy wrote: post #426

It's the same reason why I have, for more than a decade, been so frustrated with people refusing to consider proper pair programming and even mob programming, as they view the need to keep people busy churning lines of code individually as the most important part of the company. That multiple AI agents can now churn out those lines relatively nearly instantly, and yet project velocity does not go much faster, should…

> ... and yet project velocity does not go much faster

1) The models like us have finite context windows and intelligence, even with good engineering practices system complexity will eventually slow them down.

2) At the moment at least, the code still needs to be reviewed and signed off by us and reading someone else's code is usually harder than writing it.

Re: AI adoption and Solow's productivity paradox

#433

Post by stephenr »

tabs_or_spaces wrote: post #218

My experience has been * If I don't know how to do something, llms can get me started really fast. Basically it distills the time taken to research something to a small amount. * if I know something well, I find myself trying to guide the llm to make the best decisions. I haven't reached the state of completely letting go and trusting the llm yet, because the llm doesn't make good long term decisions * when working a…

> llms can get me started really fast. Basically it distills the time taken to research something

> the llm doesn't make good long term decisions

What could possibly go wrong, using something you know makes bad decisions, as the basis of your learning something new.

It's like if a dietician instructed a client to go watch McDonald's staff, when they ask how to cook the type of meals that have been recommended.

Re: AI adoption and Solow's productivity paradox

#434

Post by Ukv »

concats wrote: post #400

If we assume people are somewhat rational (big ask I know), and the Efficient-market hypothesis, then we can estimate the value created by AI to be roughly equal to the revenue of these AI companies. That is: A professional who pays 20€/month likely believes that the AI product provides them with roughly 20€ each month in productivity gains, or else they wouldn't be paying, and similarly they would pay more for a big…

> A professional who pays 20€/month likely believes that the AI product provides them with roughly 20€ each month in productivity gains, or else [...] they would pay more for a bigger subscription

Unless I'm misunderstanding, shouldn't someone rational want to pay where (value - cost) is highest, opposed to increasing cost to the point where it equals value (which has diminishing returns)?

A $40 subscription creating $1000 worth of value would be preferred over a $200 subscription creating $1100 of value, for instance, and both preferred over a $1200 subscription creating $1200 of value.

Re: AI adoption and Solow's productivity paradox

#435

Post by stackbutterflow »

slopinthebag wrote: post #169
whynotminot wrote: post #143

Earlier quoted context omitted.

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 expec…

> I see people thinking modern AI models can’t generate working code. Really? Can you show any examples of someone claiming AI models cannot generate working code? I haven't seen anyone make that claim in years, even from the most skeptical critics.

10 days ago someone was making this claim about copilot on legacy code: https://news.ycombinator.com/item?id=46932609

> Github Copilot has been great in getting that code coverage up marginally but ass otherwise.

Re: AI adoption and Solow's productivity paradox

#436

Post by mikkupikku »

y42 wrote: post #331
torben-friis wrote: post #42

Earlier quoted context omitted.

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…

Problem is, that just having a Claude subscription doesn't make you productive. Most of those talks happen in a "tech'ish" environments. Not every business is about coding. Real life example: A client came to me asking how to compare orders against order confirmation from the vendor. They come as PDF files. Which made me wonder: Wait, you don't have any kind of API or at least structured data that the vendor gives yo…

Thing is, unless the order confirmations number high in the thousands, most businesses could just hire an old lady with secretary experience to crunch through that work manually for a fraction of what it would cost them to get the whole system automated.

I've seen this play out with time sheets. Every day factory floor workers write up every job they do on time sheets, paper and pencil, but management wants excel spreadsheets with pretty plots. Solution? One old typist who can type up all the time sheets every day. No OCR trouble, no expensive developer time, if she encounters illegible numbers she just cross references against the job fliers to figure it out instead of throwing errors the first time a 0 looks like a 6.

Re: AI adoption and Solow's productivity paradox

#437

Post by crispyambulance »

I accept that AI-mediated productivity might not be what we expect to be.

But really, are CEO's the best people to assess productivity? What do they _actually_ use to measure it? Annual reviews? GTFO. Perhaps more importantly, it's not like anything a C-level says can ever be taken at face value when it involved their own business.

Re: AI adoption and Solow's productivity paradox

#438

Post by naasking »

t43562 wrote: post #359
majormajor wrote: post #250

Earlier quoted context omitted.

Coding is a relatively verifiable and strict task: it has to pass the compiler, it has to pass the test suite, it has to meet the user's requests. There are a lot of white-collar tasks that have far lower quality and correctness bars. "Researching" by plugging things into google. Writing reports summarizing how a trend that an exec saw a report on can be applied to the company. Generating new values to share at a com…

Code may have to compile but that's a lowish bar and since the AI is writing the tests it's obvious that they're going to pass. In all areas where there's less easy ways to judge output there is going to be correspondingly more value to getting "good" people. Some AI that can produce readable reports isn't "good" - what matters is the quality of the work and the insight put into it which can only be ensured by lookin…

> since the AI is writing the tests it's obvious that they're going to pass

That's not obvious at all if the AI writing the tests is different than the AI writing the code being tested. Put into an adversarial and critical mode, the same model outputs very different results.

Re: AI adoption and Solow's productivity paradox

#439

Post by simiones »

thesmtsolver2 wrote: post #177
bubblewand wrote: post #113

Earlier quoted context omitted.

What counts as “concretely”? And I don’t recall it calling sales bullshit. It identified advertising as part of the category that it classed as heavily-bullshit-jobs for reason of being zero-sum—your competitor spends more, so you spent more to avoid falling behind, standard red queen’s race. (Another in this category was the military, which is kinda the classic case of this—see also, the Missile Gap, the dreadnought…

How does that make advertising a bullshit job? The only way advertising won't exist or won't be needed is when humanity becomes a hive mind and removes all competition.

Countries can just ban advertising, and hopefully we will slowly move towards this. There are already quite a few specific bans - tobacco advertising is banned, gambling and sex product advertising is only allowed in certain specific situations, billboards and other forms of advertising on public spaces are often banned in large European cities, and so on.

Re: AI adoption and Solow's productivity paradox

#440

Post by u1hcw9nx »

torben-friis wrote: post #42
crazygringo wrote: post #21

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 benef…

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 crazygringo mispresents Solow paradox. None of the main explanations say it's the cost that removed the productivity.
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