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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

#11

Post by DaedalusII »

tehjoker wrote: post #4

There is probably a threshold effect above which the technology begins to be very useful for production (other than faking school assignments, one-off-scripts, spam, language translation, and political propaganda), but I guess we're not there yet. I'm not counting out the possibility of researchers finding a way to add long term memory or stronger reasoning abilities, which would change the game in a very disorientin…

the greatest step change will be when mainstream business realise they can use AI to accurately fill in PDF documents with information in any format

filling in pdf documents is effectively the job of millions of people around the world

Re: AI adoption and Solow's productivity paradox

#12

Post by sebmellen »

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 business/bullshit job (ala Graeber) work is meeting with people, “aligning expectations”, getting consensus, making slides/decks to communicate those thoughts, thinking about market positioning, etc.

Maybe tools like Cowork can help to find files, identify tickets, pull in information, write Excel formulas, etc.

What’s different about coding is no one actually cares about code as output from a business standpoint. The code is the end destination for decided business processes. I think, for that reason, that code is uniquely well adapted to LLM takeover.

But I’m not so sure about other white-collar jobs. If anything, AI tooling just makes everyone move faster. But an LLM automating a new feature release and drafting a press release and hopping on a sales call to sell the product is (IMO) further off than turning a detailed prompt into a fully functional codebase autonomously.

Re: AI adoption and Solow's productivity paradox

#15

Post by throwawaysleep »

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

Or give them a stick with twine and a plastic fork as a hook, as is the case with Copilot.

Re: AI adoption and Solow's productivity paradox

#16

Post by pram »

It’s funny because at work we have paid Codex and Claude but I rarely find a use for it, yet I pay for the $200 Max plan for personal stuff and will use it for hours!

So I’m not even in the “it’s useless” camp, but it’s frankly only situationally useful outside of new greenfield stuff. Maybe that is the problem?

Re: AI adoption and Solow's productivity paradox

#17

Post by DaedalusII »

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…

when the work involves navigating a bunch of rules with very ambiguous syntax, AI will automate them to the point computers automated rules based systems with very precise syntax in the 1990s

https://hazel.ai/tax-planning

this software (which i am not related to or promoting) is better at investment planning and tax planning than over 90% of RIAs in the US. It will automate RIA to the point that trading software automated stock broking. This will reduce the average RIA fee from 1% per year to 0.20% or even 0.10% per year just like mutual fund fees dropped in the early 00s

Re: AI adoption and Solow's productivity paradox

#18

Post by throwawaysleep »

SilverElfin wrote: post #14

These surveys don’t make sense. Ask the forward thinking companies and they’ll say the opposite. The flood of anti AI productivity articles almost feel like they’re meant to lull the population into not seeing what’s about to happen to employment.

Eh, try using Microsoft Copilot in Word or PowerPoint. It is worthless. If your experience with AI was a Microsoft product, you would think it was a scam too.

Re: AI adoption and Solow's productivity paradox

#19

Post by yodsanklai »

chaos_emergent wrote: post #6
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

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'm a SWE who's been using coding agents daily for the last 6 months and I'm still skeptical.

For my team at least, the productivity boost is difficult to quantify objectively. Our products and services have still tons of issues that AI isn't going to solve magically.

It's pretty clear that AI is allowing to move faster for some tasks, but it's also detrimental for other things. We're going to learn how to use these tools more efficiently, but right now, I'm not convinced about the productivity gain.

Re: AI adoption and Solow's productivity paradox

#20

Post by Haven880 »

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.

I think both. Most organizatuons lack someone like Steve Jobs to prime their product lines. Microsoft is a good example where you see their products over the years are mostly meh. Then meetings are pervasive and even more so in most companies due to msteam convenience. But currently they faced reduced demands due softer market as compare 2-3 years ago. If you observed that no effect while they layoff many and revenue still hold or at least no negative growth, I would surmise that AI is helping. But in corporate, it only counta if directly contributed sales numbers.
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