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AI adoption and Solow's productivity paradox

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Re: AI adoption and Solow's productivity paradox

#151

Post by toraway »

nradov wrote: post #136
hattmall wrote: post #93

Earlier quoted context omitted.

I find that highly unlikely, coding is the AIs best value use case by far. Right now office workers see marginal benefits but it's not like it's an order of magnitude difference. AI drafts an email, you have to check and edit it, then send it. In many cases it's a toss up if that actually saved time, and then if it did, it's not like the pace of work is break neck anyway, so the benefit is some office workers have a…

LLMs might not save time but they certainly increase quality for at least some office work. I frequently use it to check my work before sending to colleagues or customers and it occasionally catches gaps or errors in my writing.

But that idealized example could also be offset by another employee who doubles their own output by churning out lower-quality unreviewed workslop all day without checking anything, while wasting other people's time.

Re: AI adoption and Solow's productivity paradox

#152

Post by beart »

jurschreuder wrote: post #124

Workers may see the LLM as a productivity boost because they can basically cheat a their homework. As a CEO I see it as a massive clog up of vast amounts of content that somebody will need to check. A DDoS of any text-based system. The other day I got a document of 155 pages in Whatsapp. Thanx. Same with pull requests. Who will check all this?

> Who will check all this?

The answer to that, for some, is more AI.

I had a peer explain that the PRs created by AI are now too large and difficult to understand. They were concerned that bugs would crop up after merging the code. Their solution, was to use another AI to review the code... However, this did not solve the problem of not knowing what the code does. They had a solution for that as well... ask AI to prepare a quiz and then deliver it to the engineer to check their understanding of the code.

The question was asked - does using AI mean best-practices should no longer be followed? There were some in the conversation who answered, "probably yes".

> Who will check all this?

So yeah, I think the real answer to that is... no one.

Re: AI adoption and Solow's productivity paradox

#153

Post by [deleted] »

LPisGood wrote: post #31
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 alre…

[deleted]

Re: AI adoption and Solow's productivity paradox

#155

Post by oblio »

DaedalusII wrote: post #10
chaos_emergent wrote: post #6

Earlier quoted context omitted.

100% All of the people who are floored by AI capabilities right now are software engineers, and everyone who's extremely skeptical basically has any other office job. On investigating their primary AI interaction surface, it's Microsoft Co-Pilot, which has to be the absolute shittiest implementation of any AI system so far. As a progress-driven person, it's just super disappointing to see how few people are benefitin…

I think anthropic will succeed immensely here because when integrated with Microsoft365 and especially Excel it basically does what co-pilot said it would do. The moment of realisation happen for a lot of normoid business people when they see claude make a DCF spreadsheet or search emails claude is also smart because it visually shows the user as it resizes the columns, changes colours, etc. Seeing the computer do th…

> normoid

Do you work extra hard to be this arrogant or does it come naturally?

Re: AI adoption and Solow's productivity paradox

#156

Post by harrall »

whynotminot wrote: post #143
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…

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’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.

Re: AI adoption and Solow's productivity paradox

#157

Post by ccortes »

Aurornis wrote: post #132
abraxas wrote: post #64

Earlier quoted context omitted.

What if LLMs are optimizing the average office worker's productivity but the work itself simply has no discernable economic value? This is argued at length in Grebber's Bullshit Jobs essay and book.

> but the work itself simply has no discernable economic value? This is argued at length in Grebber's Bullshit Jobs essay and book. That book was very different than what I expected from all of the internet comment takes about it. The premise was really thin and did't actually support the idea that the jobs don't generate value. It was comparing to a hypothetical world where everything is perfectly organized, everyon…

> It was comparing to a hypothetical world where everything is perfectly organized, everyone is perfectly behaved, everything is perfectly ordered, and therefore we don't have to have certain jobs that only exist to counter other imperfect things in society.

> Jobs that don't provide value for a company are cut, eventually.

Uhm, seems like Greaber is not the only one drawing conclusions from a hypothetical perfect world

Re: AI adoption and Solow's productivity paradox

#158

Post by simonw »

tverbeure wrote: post #104
simonw wrote: post #61

Earlier quoted context omitted.

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 in…

Nobody questions that Anthropic makes revenue from a $20 subscription. The opposite would be very strange.

A lot of people believe that Anthropic lose money selling tokens to customers because they are subsidizing it for growth.

Re: AI adoption and Solow's productivity paradox

#159

Post by simonw »

Esophagus4 wrote: post #68
simonw wrote: post #61

Earlier quoted context omitted.

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 in…

I always assumed that with inference being so cheap, my subscription fees were paying for training costs, not inference.

Anthropic and OpenAI are both well documented as losing billions of dollars a year because their revenue doesn't cover their R&D and training costs, but that doesn't mean their revenue doesn't cover their inference costs.

Re: AI adoption and Solow's productivity paradox

#160

Post by ccortes »

nradov wrote: post #133
abraxas wrote: post #64

Earlier quoted context omitted.

What if LLMs are optimizing the average office worker's productivity but the work itself simply has no discernable economic value? This is argued at length in Grebber's Bullshit Jobs essay and book.

Bullshit Jobs is one of those "just so" stories that seems truthy but doesn't stand up to any critical evaluation. Companies are obviously not hesitant to lay off unproductive workers. While in large enterprises there is some level of empire building where managers hire more workers than necessary just to inflate their own importance, in the long run those businesses fall to leaner competitors.

> in the long run those businesses fall to leaner competitors

This is not true at all. You can find plenty of examples going either way but it’s far from truth from being a universal reality

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