On the other hand, "zero or small negative effects on the most experienced/most able workers".
In other words, if you're skilled, there's nothing AI can do for you…
To be concrete about it, I recently ported a project from SwiftUI on iOS (an ecosystem I am very comfortable with) to an Android app written in Kotlin (an ecosystem I mostly dread). I don't find ChatGPT very helpful with my day-to-day Swift stuff, but it was incredibly helpful with the Android work, from language syntax to idioms to outright translation of code.
I tried using the Bing chat interface, and it repeatedly pushed me in the direction of using Microsoft tools to accomplish tasks for a cross-compile mid tier solution. I had to explicitly tell it to exclude them.
In areas where I'm an expert, I find myself correcting ChatGPT constantly. But for a language I want to learn, it's been really helpful to get me started on a simple algorithm or debug an error message.
Think about that…
In practice, my coworkers call me to find and then explain solutions to them.
I don’t see this changing with AIs. Having a “super Google” is great… for people already comfortable with such tools and capable of using them.
My coworkers will now ask me to ask the AI… on their… behalf.
OMG! I’m going to turn into Lieutenant Tawny Madison: https://chat.openai.com/share/0efbca4d-9e33-4af0-9ed6-2f8821...
I don't think you grasp how this will play out over multi-game
While I agree with your assessment on wage pressure, the folks this is going to hurt the most are the new graduates that don't have the knowledge or experience. Their competition just got a whole lot stiffer.
It benefits two groups the most, someone with literally zero experience and experts.
What matters is which of these strategies will result in actual success. This is honestly far too hard to tell at this point.
I'll say here, I've spoken to and spent time with a few well known billionaires and I'd say deep down, they are exterminists no matter how nice a face they try to put on it. Over time they just come to believe most people don't matter at all. Its really dark, and the sooner we come to terms with that the better.
Just think of when Photoshop 4.0 added layers and now composing was for everyone, not just for those venturing into channel operations… (To be fair, here, things got much easier even for those who managed previously without this.)
Yet...
If the task you are working on is phone support. If you are a dev, you are perpetually learning new things, it's not possible to memorise the whole field so AI would have more opportunity to help.
> "Customer support agents using an AI tool to guide their conversations saw a nearly 14 percent increase in [overall] productivity, with 35 percent improvements for the lowest skilled and least experienced workers, and zero or small negative effects on the most experienced/most able workers... [out of] 5,000 agents working for a Fortune 500 software company."
AI quality is somewhere in the middle between highly skilled and neophyte (at present anyway).
AI will further consolidate mega corp power to a terrifying degree.
Consider the relationship between atmospheric nuclear testing and low-background steel [1] but for AI and older workers whose knowledge predates the introduction of LLMs in the workforce.
My guess though is that high skilled workers remain far more productive than AI-augmented low skilled workers.
Elaborating further on the idea of productivity, as I said above, this doesn’t make employees more productive. It is doing some of the producing. It is not like an improved tool, where someone has to operate it to reap the benefits. It “upgrades productivity” more like how a kiosk at a McDonald’s upgrades productivity - not of the worker, but of the business. And much like the kiosks, we would be naive to believe they won’t replace the humans in due time.
This also has larger consequences for knowledge workers. Previously, to attain a higher level of productivity out of a worker, companies would have to invest in them so they could develop the necessary skills. Gone (or at least lessened) is that need. So workers will have less skill, less job freedom, a smaller share of profit, less social mobility. This is a nightmare for the working class.
Absolutely no one is spending tens of millions of dollars developing these tools in order to let random plebs capture much of the value produced by them.
This coming century is supposed to be about 'Rest of World' - first China, then India and the rest.
But it's going to risk the ability of the nearly-unskilled labour to help.
They can learn new things and cover over the things they do now know. Hopefully they can join the Developed World quickly.
Every time someone says X is going to suffer under ChatGPT, I remind that person that X will also improve their productivity by using ChatGPT.
ChatGPT is the most amazing personal tutor I can find. I'm adding 1 IT cert per month, largely due to ChatGPT's help as my personal tutor.
Do you know what happened to manufacturing when automation low-cost outsourcing happened?
It was wiped out.
It was devastating for certain sectors of the economy, even as 'net productivity rose' - the surpluses were acquired by some, not others.
A lot of 'ghettos' in the US are a direct result of mass factory closures.
Now - imagine that happening over the developing world, or rather, factories that were supposed to open, never did.
The developing world are 'services export' economy, with things like call centres etc. - and AI will more likely than not just evaporate those roles.
That those people will have 'access to ChatGPT' is besides the point when most of them don't even have computers (just mobile phones), or any way to apply that knowledge.
It's a bit like saying: 'The developing world has access to Wikipedia and all of Harvard courses online! They should all have great jobs!'
Unfortunately that's not how it works.
AI is going to help white collar workers, not pink or blue collar work which is low-skilled.
Yes, but mostly from the companies developing these products:
* The CoPilot productivity study by Peng et al. that is summarized in a Blog post [1] with some additional details in the Arxiv preprint [2]. They find "developers who used GitHub Copilot completed the task significantly faster–55% faster than the developers who didn’t use GitHub Copilot". (Grep for "but speed is important, too" in [1].)
* Amazon's Q1 earnings report [3] includes a paragraph stating that "participants [using] CodeWhisperer completed tasks 57% faster (on average) and were 27% more likely to complete them successfully than those who didn’t use CodeWhisperer.
* I seem to remember seeing something on Replit's blog a while back with a similar number, but can't find it anymore, so maybe I'm mistaken.
These speed numbers are on specific and well-specified programming tasks, which is of course only one part of a developer's job, so there's a lot of opportunity for impactful research in this space. I suspect that the Empirical Software Engineering community will be awash in third-party empirical studies asking all sorts of more specific productivity questions by this time next year.
[1] https://github.blog/2022-09-07-research-quantifying-github-c...
[2] https://arxiv.org/pdf/2302.06590.pdf
[3] https://s2.q4cdn.com/299287126/files/doc_financials/2023/q1/...
> The tool was rolled out to the agents gradually, mostly between November 2020 and February 2021.
So the 14% gain came from vastly less capable systems than what we now have today.
When copilot was released, I’d say I got a 15% increase. When ChatGPT was released it was like 50% at least and I can’t imagine going back. I remember how slow it was now.
My advice would be to force yourself to leverage it more or something. I hate googling now. I’ll find a page, copy the entire thing into gpt4 and the file i’m using with the error message and i have to do nothing.
How are y’all using it?
> I’ll find a page, copy the entire thing into gpt4 and the file i’m using with the error message and i have to do nothing.
can you explain more about this I don't quite understand this passage.
Have there been any good studies on programmer productivity? 14% would be a blip in the constant flow of productivity-enhancing language, tools, architectures etc. that have been steady accelerating the pace and scale of development for decades ...