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.
The layoffs you see now are due to offshoring disguised as AI taking over. Google, Amazon, and even Hollywood are getting in on the offshoring craze.
Yup, Claude Opus 4.5 + Claude Code feels like its teetering right on the edge of Jevon's Paradox. It can't work alone, and it needs human design and code review, if only to ensure it understands the problem and produces maintainable code. But it can build very credible drafts of entire features based on a couple of hours of planning, then I can spend a day reading closely and tweaking for quality. But the code? It's professional work, and I've worked with contractors who did a lot worse.
So right now? Opus 4.5 feels like an enormous productivity booster for existing developers (which may indirectly create unemployment or increase the demand for software enough to create jobs), but it can't work on large projects on an ongoing basis without a knowledgeable human. So it's more like a tractor than anything else: It might cause programmer unemployment, but eh, life happens.
But I can increasingly see that it would only take about one more breakthrough, and next gen AI models might make enormous categories of human intellectual labor about as obsolete as the buggy whip. If you could get a Stanford grad for a couple of dollars an hour, what would the humans actually do? (Manual labor will be replaced slower. Rod Brooks from the MIT AI Lab had a long article recently on state of robotics, and it sounds like they are still heavily handicapped by inadequate hardware: https://rodneybrooks.com/why-todays-humanoids-wont-learn-dex... )
Jevon's Paradox and comparative advantage won't protect you forever if you effectively create a "competitor species" with better price-performance across the board. That's what happened to the chimps and Homo neanderthalensis. And they didn't exactly see a lot of economic benefits from the rise of Homo sapiens, you know?
Just take one long look at the kind of utter garbage human mind has to work with. It's a frame that, without a hideous amount of wetware doing data processing, can't even keep its own limbs tracked - because proprioreception is made of wet meat noise and integration error. Smartphones in 2010 shipped with better IMUs, and today's smartphones ship with better cameras.
Modern robot frames just have a different set of tradeoffs from the human body. They're well into "good enough" overall. But we are yet to make a general purpose AI that would be able to do "universal robot" things. We can't even do it in a sim with perfect sensors and actuators.
His hardware argument is primarily sensory. Specifically, current generation robots, no matter how clever they might be, have a physical sensorium that's incredibly impoverished, about on par with a human with severe frostbite. Even if you try to use humans as teleoperators, it's incredibly awkward and frustrating, and they have to massively over-rely on vision. And fine-detail manual dexterity is hopeless. When you can see someone teleoperate a robot and knit a patterned hat, or even detach two stuck Lego bricks, then robots will have the sensors needed for human-level dexterity.
Again: we can't even make a universal robot work in a sim with perfect sensor streams! If the issue was "universal robots work fine in sims, suffer in real world", then his argument would have had a leg to stand on. As is? It's a "robot AI caught lacking" problem - and ignoring the elephant in the room in favor of nitpicking at hardware isn't doing anyone a favor.
It's not like we don't know how to make sensors. Wrist-mounted cameras cover a multitude of sins, if your AI knows how to leverage them - they give you a data stream about as rich as anything a human gets from the skin - and every single motor in a robot is a force feedback sensor, giving it a rudimentary sense of touch.
Nothing stops you from getting more of that with dedicated piezos, if you want better "touchy-feely" capabilities. But do you want to? We are nowhere near being limited by "robot skin isn't good enough". We are at "if we made a perfect replica of a human hand for a robot to work with, it wouldn't allow us to do anything we can't already do". The bottleneck lies elsewhere.
AI is just the other pincer that will finish the kill shot.
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.)
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'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?
In many of these discussions that line seems to get blurred and I start to get the impression people are using the specter of a vague, poorly understood hypothetical future problem to argue for concrete societal changes now.
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.
Isn't ending all those programs one of the core ideas of universal basic income? Instead of having a huge bureaucracy administering targeted social welfare you cut all the overhead and just pay everyone enough to exist, regardless of whether you actually need it. It'd still be more expensive, but giving people something dependable to fall back on would hopefully increase innovation and entrepreneurship, offsetting some of the costs
Can we stop pretending with the word "fair"? If you want to squeeze out more money then you do it by force. It's not "fair". It's just "we can do this".
They report no improvements on any measured outcome. Not lower stress, not more education, not better health. They work a bit less but that doesn't help them or their kids.
Over the long term it harms them because their productive skills, values, and emotional capacities atrophy away from lack of use.
That's extremely interesting, can you link such studies?
It's one of those things that can be tricky to research because almost all the researchers and journalists on the topic very much don't want to see this conclusion. So there's a tremendous amount of misrepresentation and wishful reasoning about how to interpret the data. The truth comes out from actually reading the data, not researcher or journalist summaries.
https://yle.fi/a/3-11337944 https://www.helsinki.fi/en/news/fair-society/universal-basic...
so basic income caused more happiness, less stress. but those are not profitable things, so, no basic income in finland.
You could ban it and then turn all existing employment into a makework jobs program, but this doesn’t seem sustainable: work you know is pointless is just as psychically corrosive, and in any event companies will just leave for less-regulated shores where AI is allowed.
Yes, but not for the reasons you state. It harms them because we have an zero desire as a society to effectively combat inflation, which negates any benefits we can give people who receive the basic income.
The powers-that-be don't take action to make sure the people who get basic income can actually use it to improve their lives. Food prices rapidly inflate, education costs skyrocket, medical costs increase exponentially almost overnight.
Much like how the government backstopping student loans basically got university costs to jump, promising to give people a basic income while not addressing the root causes of inequality and wealth disparity just makes things worse.
If you want basic income to truly work, you have to engage in some activities in the short term that are inherently un-capitalistic, although if done correctly, actually improve capitalism as a whole for society. Price controls and freezes, slashing executive pay, increasing taxes on the wealthiest, etc.
My grandmother was born in 1924 and died in 2019 please appreciate how much change she had to adapt to over that period
She never learned how to type on a keyboard so you do the math
What you’re not counting is all of the millions of people who died because they couldn’t actually adapt to the new world
Which is fine but they didn’t need to be killed, they just became irrelevant and went away
On old people who can't or don't work.
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).
In French we say "With "ifs" you can put Paris in a bottle."
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.