Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

AI adoption and Solow's productivity paradox

fortune.com

Post reply on HN
Print view View original

31–40 of 783 posts

Re: AI adoption and Solow's productivity paradox

#31

Post by LPisGood »

sebmellen wrote: post #12

The thing with a lot of white collar work is that the thinking/talking is often the majority of the work… unlike coding, where thinking is (or, used to be, pre-agent) a smaller percentage of the time consumed. Writing the software, which is essentially working through how to implement the thought, used to take a much larger percentage of the overall time consumed from thought to completion. Other white collar busines…

I’m confused what kind of software engineer jobs there are that don’t involve meeting with people, “aligning expectations”, getting consensus, making slides/decks to communicate that, thinking about market positioning, etc?

If you weren’t doing much of that before, I struggled to think of how you were doing much engineering at all, save some more niche extremely technical roles where many of those questions were already answered, but even still, I should expect you’re having those kinds of discussions, just more efficiently and with other engineers.

Re: AI adoption and Solow's productivity paradox

#32

Post by sebmellen »

lich_king wrote: post #22
sebmellen wrote: post #12

The thing with a lot of white collar work is that the thinking/talking is often the majority of the work… unlike coding, where thinking is (or, used to be, pre-agent) a smaller percentage of the time consumed. Writing the software, which is essentially working through how to implement the thought, used to take a much larger percentage of the overall time consumed from thought to completion. Other white collar busines…

> making slides/decks to communicate those thoughts, That use case is definitely delegated to LLMs by many people. That said, I don't think it translates into linear productivity gains. Most white collar work isn't so fast-paced that if you save an hour making slides, you're going to reap some big productivity benefit. What are you going to do, make five more decks about the same thing? Respond to every email twice?…

Yeah, but this is self-correcting. Eventually it will get to a point where the data that you use to prompt the LLM will have more signal than the LLM output.

But if you get deep into an enterprise, you'll find there are so many irreducible complexities (as Stephen Wolfram might coin them), that you really need a fully agentically empowered worker — meaning a human — to make progress. AI is not there yet.

Re: AI adoption and Solow's productivity paradox

#33

Post by kjellsbells »

Herring wrote: post #9

My compsci brain suggests large orgs are a distributed system running on faulty hardware (humans) with high network latency (communication). The individual people (CPUs) are plenty fast, we just waste time in meetings, or waiting for approval, or a lot of tasks can't be parallelized, etc. Before upgrading, you need to know if you're I/O Bound vs CPU Bound.

Maybe experienced people are the L2 cache? And the challenge is to keep the cache fresh and not too deep. You want institutional memory available quickly (cache hit) to help with whatever your CPU people need at that instant. If you don´t have a cache, you can still solve the problem, but oof, is it gonna take you a long time. OTOH, if you get bad data in the cache, that is not good, as everyone is going be picking that out of the cache instead of really figuring out what to do.

Re: AI adoption and Solow's productivity paradox

#34

Post by carefree-bob »

It's not just technology, it's very hard to detect the effect of inventions in general on productivity. There was a paper pointing out that the invention of the steam engine was basically invisible in the productivity statistics:

https://www.frbsf.org/wp-content/uploads/crafts.pdf

Re: AI adoption and Solow's productivity paradox

#35

Post by Herring »

amrocha wrote: post #26
Herring wrote: post #9

My compsci brain suggests large orgs are a distributed system running on faulty hardware (humans) with high network latency (communication). The individual people (CPUs) are plenty fast, we just waste time in meetings, or waiting for approval, or a lot of tasks can't be parallelized, etc. Before upgrading, you need to know if you're I/O Bound vs CPU Bound.

Then where are all the amazing open source programs written by individuals by themselves? Where are all the small businesses supposedly assisted by AI?

> 4% of GitHub public commits are being authored by Claude Code right now. At the current trajectory, we believe that Claude Code will be 20%+ of all daily commits by the end of 2026.

https://newsletter.semianalysis.com/p/claude-code-is-the-inf...

Re: AI adoption and Solow's productivity paradox

#36

Post by conductr »

jeron wrote: post #5
DaedalusII wrote: post #3

If you include microsoft copilot trials in fortune 500s, absolutely. A lot of major listed companies are still oblivious to the functionality of AI, their senior management don't even use it out of laziness

it turns out it's really hard to get a man to fish with a pole when you don't teach them how to use the reel

In regards to copilot, they’ve also been led on a fishing expedition to the middle of a desert

Re: AI adoption and Solow's productivity paradox

#37

Post by beloch »

The article suggests that AI-related productivity gains could follow a J-curve. An initial decline, as initially happened with IT, followed by an exponential surge. They admit this is heavily dependent on the real value AI provides.

However, there's another factor. The J-curve for IT happened in a different era. No matter when you jumped on the bandwagon, things just kept getting faster, easier, and cheaper. Moore's law was relentless. The exponential growth phase of the J-curve for AI, if there is one, is going to be heavily damped by the enshitification phase of the winning AI companies. They are currently incurring massive debt in order to gain an edge on their competition. Whatever companies are left standing in a couple of years are going to have to raise the funds to service and pay back that debt. The investment required to compete in AI is so massive that cheaper competition may not arise, and a small number of (or single) winner could put anyone dependent on AI into a financial bind. Will growth really be exponential if this happens and the benefits aren't clearly worth it?

The best possible outcome may be for the bubble to pop, the current batch of AI companies to go bankrupt, and for AI capability to be built back better and cheaper as computation becomes cheaper.

Re: AI adoption and Solow's productivity paradox

#38

Post by mr_toad »

bubblewand wrote: post #7

My company’s behind the curve, just got nudged today that I should make sure my AI use numbers aren’t low enough to stand out or I may have a bad time. Reckon we’re minimum six months from “oh whoops that was a waste of money”, maybe even a year. (Unless the AI market very publicly crashes first)

So management basically have no clue and want you to figure out how to use AI?

Do they also make you write your own performance review and set your own objectives?

Re: AI adoption and Solow's productivity paradox

#39

Post by kamaal »

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…

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.

Re: AI adoption and Solow's productivity paradox

#40

Post by com2kid »

amrocha wrote: post #26
Herring wrote: post #9

My compsci brain suggests large orgs are a distributed system running on faulty hardware (humans) with high network latency (communication). The individual people (CPUs) are plenty fast, we just waste time in meetings, or waiting for approval, or a lot of tasks can't be parallelized, etc. Before upgrading, you need to know if you're I/O Bound vs CPU Bound.

Then where are all the amazing open source programs written by individuals by themselves? Where are all the small businesses supposedly assisted by AI?

Seemingly every day on Show HN?

Also small businesses aren't going to publish blog posts saying "we saved $500 on graphic design this week!"

Post reply on HN