alt Hacker NewsThis argument hinges rather strongly on whether or not AI is going to create a broad, durable, and lasting unemployment effect.
Tractors did not cause this phenomenon because jevons paradox kicked in and induced demand rendered the problem moot, or demand eventually exceeded what mere tractors were capable of doing for agricultural productivity.
The same can probably be said for contemporary AI, but it's tough to tell right now. There's some scant indications we've scaled LLMs as far as they can go without another fundamental discovery similar to the attention paper in 2017. GPT-5 was underwhelming, and each new Claude Opus is an incremental improvement at best, still unable to execute an entire business idea from a single prompt. If we don't continue to see large leaps in capability like circa 2021-2022, then it can be argued jevons paradox will kick in here and at best LLMs will be a productivity multiplier for already experienced white collar workers - not a replacement for them.
All this being said, technological unemployment is not something that will be sudden or obvious, nor will human innovation always stay under jevons paradox, and I think policymakers need to seriously entertain taboo solutions for it sooner or later. Such as a WPA-style infrastructure project or basic income.
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> This argument hinges rather strongly on whether or not AI is going to create a broad, durable, and lasting unemployment effect.
I think GP's argument makes a pretty strong case that it won't, even if AI somehow successfully automates 99% of all currently existing tasks. We automated away 99% of jobs once during the agricultural revolution and it didn't result in "a broad, durable, and lasting unemployment effect" then. Quite the opposite in fact.
Maybe if AI actually automates 100% of everything then we'll need to think about this more. But that seems unlikely to happen anytime in the foreseeable future given the current trajectory of the technology. (Even 50% seems unlikely.)
> The same can probably be said for contemporary AI, but it's tough to tell right now
The same can't even be said for contemporary AI, because lots of the jobs it's going to replace are theoretical or hype. Self-driving cars should've been here years ago, but because AI is extremely hard to improve upon once it gets to a certain level of efficacy, they haven't happened.
The question is: should we be discussing this stuff when AI hasn't started taking all those jobs yet?
When most of the human population were farmers should we have taxed advances in agriculture which destroyed the everybody’s job?
> each new Claude Opus is an incremental improvement at best, still unable to execute an entire business idea from a single prompt.
If your way of evaluating the progress of AI is a binary one, then you'll see no progress at all until suddenly it passes that bar.
But seeing that we do have incremental improvements on essentially all evals (and my own experience), even if it takes another decade we should be planning for it now. Even if it does require an entirely fundamental breakthrough like the attention paper, given the amount of researchers working on it, and capital devoted to it, I wouldn't put any money against such a breakthrough arriving before long.
>The same can probably be said for contemporary AI, but it's tough to tell right now. There's some scant indications we've scaled LLMs as far as they can go without another fundamental discovery similar to the attention paper in 2017. GPT-5 was underwhelming, and each new Claude Opus is an incremental improvement at best, still unable to execute an entire business idea from a single prompt. If we don't continue to see large leaps in capability like circa 2021-2022, then it can be argued jevons paradox will kick in here and at best LLMs will be a productivity multiplier for already experienced white collar workers - not a replacement for them.
The NBA has an incredibly high demand for 14-foot-tall basketball players, but none have shown up to apply. Similarly, if this causes our economy to increase demand for people to "execute an entire business ide from a single prompt", it does not mean unemployment can be alleviated by moving all the jobless into roles like that.
We don't need science fiction AI that will put everyone out of work for it to be ruinous. We only need half-assed AI good enough that they don't want to pay a burgerflipper to flip burgers anymore, and it'll all go to hell.
Basic income doesn’t do anything. We already have food stamps and so on. The largest sector of US federal spending is health and social welfare. We’d have to end pretty much all those programs to run a minuscule basic income.
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I think you're basing AI only on modern 2025 LLMs.
If there is a magnitude increase in compute (TPUs, NPUs, etc) over the next 3-5 years then even marginal increases in LLM usability will take white collar jobs.
If there is an exponential increase in power (fusion) and compute (quantum) combined with improvements in robotics and you're in the territory where humans can entirely be replaced in all industries (blue collar, white collar, doctors, lawyers, etc).
> technological unemployment is not something that will be sudden or obvious
I already have friends experiencing technological unemployment. Programmers suddenly need backup plans. Several designers I know are changing careers. Not to mention, the voiceover artist profession will probably cease to exist besides this last batch of known voices. Writer, editor - these were dependable careers for friends, once. A friend travelled the world and did freelance copyediting for large clients.
ChatGPT was just released three years ago.