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AI adoption and Solow's productivity paradox

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Re: AI adoption and Solow's productivity paradox

#261
post #64

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…

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.

We made an under-the-radar optimization in a data flow in my company. A given task is now much more freshData-assisted that it used to.

Was a LLM used during that optimization? Yes.

Who will correlate the sudden productivity improvement with our optimization of the data flow with the availability of a LLM to do such optimizations fast enough that no project+consultants+management is needed ?

No one.

Just like no one is evaluating the value of a hammer or a ladder when you build a house.

Re: AI adoption and Solow's productivity paradox

#262
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.

In my opinion, you're very wrong. There is typically lots of good communication -- one way. The stuff that doesn't get communicated down to worker bees is intentional. "CPUs" aren't all that fast either, unless you make them by providing incentives. if you're a well paid worker who likes their job, i can see why you would think that, but most people aren't that.

Meetings are work, as much as IPC and network calls are work. Just because they're not fun, or what you like to do, it doesn't mean they're any less of a work.

I think you're analyzing things from a tactical perspective, without considering strategic considerations. For example, have you considered that it might not be desirable for CPUs to be just fast, or fast at all? is CISC faster than RISC? different architectural considerations based on different strategic goals right?

If you're an order picker at an amazon warehouse, raw speed is important. being able to execute a simpler and more fixed set of instructions (RISC), and at greater speed is more desirable. if you're an IT worker, less so. IT is generally a cost-center, except for companies that sell IT services or software. if you're in a cost center, then you exist for non-profit-related strategic reasons, such as to help the rest of the company work efficiently, be resilient, compete, be secure. Some people exist in case they're needed some day, others are needed critically but not frequently, yet others are needed frequently but not critically. being able to execute complex and critical tasks reliably and in short order is more desirable for some workers. Being fast in a human context also means being easily bored, or it could mean lots of bullshit work needs to be invented to keep the person busy and happy.

I'd suggest taking that compsci approach but considering not just the varying tasks and workloads, but also the diversity of goals and user cases of users (decision makers/managers in companies). There are deeper topics with regards or strategy and decision making surrounding the state machines of incentives and punishments, and decision maker organization (hierarchical, flat, hub-and-spoke,full-mesh,etc..).

Re: AI adoption and Solow's productivity paradox

#264

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…

In a lot of larger organizations there is a whole stable of people whose job is to keep stakeholders and programmers from ever having to talk to each other. This was considered a best practice a quarter-century ago ("Office Space" makes fun of it), and in retrospect I concede it sometimes had a point.

Re: AI adoption and Solow's productivity paradox

#265
post #228

Earlier quoted context omitted.

And it will get worse once the UX people get ahold of it.

You got that right . .. imagine AI making more keyboard shortcuts, "helping" wayland move off X more so, new window transistions, overhauling htmx ... it'll be hell+ on earth.

We can indeed only imagine. For now, AI has been a curse for open source projects.

Re: AI adoption and Solow's productivity paradox

#266

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

That's probably true for some, but I think a lot of big orgs are simply risk-averse and see AI in general as a giant risk that isn't even fully baked enough to quantify yet. The security and confidentiality issues alone will make Operations hesitant, and Legal probably has some questions about IP (both the risk of a model outputting patented or otherwise protected code, and the huge legal gray area that is the copyrightability of the output of an LLM).

Give it a year or two and let things settle down and (assuming the music is still playing at that time) you might see more dinosaurs start to wander this way.

Re: AI adoption and Solow's productivity paradox

#267

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…

The future of work is fewer human team members and way more AI assistants. I think companies will need fewer engineers but there will be more companies. Now: 100 companies who employ 1,000 engineers each What we are transitioning to: 1000 companies who employ 10 engineers each What will happen in the future: 10,000 companies who employ 1 engineer each Same number of engineers. We are about to enter an era of explosiv…

That means the system will collapse in the future. Now from bunch of people some good programmers are made. Rest go into marketing, sales, agile or other not really technical roles. When the initial crowd will be gone there will be no experienced users of AI. Crappy inexperienced developer will make more crap without prior experience and ability to judge the design decisions. Basically no seniors without juniors.

Re: AI adoption and Solow's productivity paradox

#268
post #244

Earlier quoted context omitted.

The future of work is fewer human team members and way more AI assistants. I think companies will need fewer engineers but there will be more companies. Now: 100 companies who employ 1,000 engineers each What we are transitioning to: 1000 companies who employ 10 engineers each What will happen in the future: 10,000 companies who employ 1 engineer each Same number of engineers. We are about to enter an era of explosiv…

yeah, I agree. When Engineering Budget Managers see their AI bills rising, they will fire the bottom 5-10% every 6-12 months and increase the AI assistant budget for the high performers, giving them even more leverage.

Now if only companies knew how to correctly assess actual impact and not perceived impact.

Re: AI adoption and Solow's productivity paradox

#269

Earlier quoted context omitted.

> And I don’t recall it calling sales bullshit. It says stuff like why can’t a customer just order from an online form? The employee who helps them doesn’t do anything except make them feel better. Must be a bullshit job. It talks specifically about my employees filling internal roles like this. > advertising I understand the arms race argument, but it’s really hard to see what an alternative looks like. People can s…

It's an important function in a capitalist economy. Socialist economies are like "adblock for your life". That said, some advertising can be useful to inform consumers that a good exists, but convincing them they need it by synthesizing desires or fighting off competitors? Useless and socially detrimental.

> Socialist economies are like "adblock for your life".

There's nothing inherent to socialism that would preclude advertising. It's an economic system where the means of production (capital) is owned by the workers or the state. In market socialism you still have worker cooperatives competing on the market.

Re: AI adoption and Solow's productivity paradox

#270

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…

not true at all, onboarding is complex too. E.g. you cant just connect claude to your outlook, or have it automate stuff in your CRM. As a office drone, you don't have the admin permissions to setup those connections at all.

And that's the point here: value is handicapped by the web interface, and we are stuck there for the foreseeable future until the tech teams get their priorities straight and build decent data integration layers, and workflow management platforms.

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