For my money, I used this analogy at work:
Before AI, we were trying to save money, but through a different technique: Prompting (overseas) humans.
After over a decade of trying that, we learned that had... flaws. So round 2: Prompting (smart) robots.
The job losses? This is just Offshoring 2.0; complete with everyone getting to re-learn the lessons of Offshoring 1.0.
> Prompting (overseas) humans [...] After over a decade of trying that, we learned that had... flaws.
I think this is a US-centric point of view, and seems (though I hope it's not!) slightly condescending to those of us not in the US.
Software engineering is more than what happens to US-based businesses and their leadership commanding hundreds or thousands of overseas humans. Offshoring in software is certainly a US concern (and to a lesser extent, other nations suffer it), but is NOT a universal problem of software engineering. Software engineering happens in multiple countries, and while the big money is in the US, that's not all there is to it.
Software engineering exists "natively" in countries other than the US, so any problems with it should probably (also) be framed without exclusive reference to the US.
The problem isn't that there aren't high quality offshore developers - far from it. Or even high quality AI models.
The problems are inherent with outsourcing to a 3rd party and having little oversight. Oversight is, in both cases, way harder than it appears.
The problems are actually not the oversight but the motivation: the point of outsourcing is cost-cutting, not finding equally talented developers elsewhere.
This is especially evident in manufacturing: China can produce extremely sophisticated technology with excellent quality and well thought-out design but that's not what foreign customers look for when outsourcing to China. They want cheap, so they get cheap.
"Oversight" in this case only solves the problem of the quality problems being intentionally hidden initially to get the sale. This might be where the actual parallels with AI models lie: quality of results going down after the initial launch because maintaining the quality is too expensive.
Funnily enough, I left a similar comment just the other day: https://news.ycombinator.com/item?id=44944717
The conclusion I reached was different, though. We learnt how to do outsourcing "properly" pretty quickly after some initial high-profile failures, which is why it has only continued to grow into such a huge industry. This also involved local talent refocusing on higher-value tasks, which is why job losses were limited. Those same lessons and outcomes of outsourcing are very relevant to "bot-sourcing'.
However, I do feel concerned that AI is gaining skill-levels much faster than the rate at which people can upskill themselves.
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I'm sure the blacksmiths and weavers will find solace in that take. Their time will return!