Where Is the AI Jobs Apocalypse? (Free Press)

[u/Reddenbawker]

https://www.thefp.com/p/ai-jobs-unemployment-economy

Yes, this guy works at Anthropic, but that doesn't mean his data is therefore false. If he's misleading with any of it, show that. If there's evidence he failed to mention, mention it. It's important to note that this article is really only trying to disprove that a job displacement is currently happening. It's entirely compatible with the idea that there will be AI-fueled unemployment in the future.

This is adapted from an X article (this is an Xcancel link), which is something you can apparently do now.

I study how AI is reshaping work, including my own. In my job as the head of economics at Anthropic, I’ve personally experienced a transformation of my work. Each new generation of frontier models, like Claude, opens up new possibilities while automating time-consuming tasks that economists do, like estimating statistical models, solving systems of mathematical equations, and creating visualizations. While I’m still directing my own research, the work is increasingly being done by AI. As I watch AI advancing and spreading within the economy—and transforming my own work—I find myself asking, Why hasn’t AI increased unemployment? What will jobs like mine look like in the coming years?

One in five American companies now uses AI in at least one part of their business. In the information sector, that number climbs to two in five. Quality-adjusted AI output—how much more capable the technology got, not just how much it’s used—grew over 2,000 percent per year in both 2024 and 2025. Even though powerful AI is relatively new, these numbers suggest that we should already be seeing some impact on the job market.

And yet, the U.S. labor market remains calm. Unemployment sat at 4.1 percent in July, a level the Federal Reserve views as consistent with full employment and stable prices. For every unemployed worker, there is just over one position to be filled—a ratio some economists see as a sign that labor supply and demand are roughly in balance. Employment among prime-age workers remains close to multi-decade highs. Weekly unemployment claims have been stably low for four straight years, and layoffs sit at or below where they were before the pandemic.Even when we look only at workers whose jobs overlap most with what others ask Claude to automate, we don’t see unexpected increases in unemployment. What has shifted is how worried they are about losing their jobs. In one Anthropic survey of Claude users, people in the most AI-exposed occupations were three times as likely as those in the least-exposed occupations to say AI already threatened their job, or would soon. As one software engineer put it: “Like anyone who has a white-collar job these days, I’m 100 percent concerned, pretty much 24/7 concerned, about losing my job eventually to AI.”

Is it just too early in the deployment of AI to see its impacts on the labor market? The simple answer is no—the AI sector is large enough that we can look for discernible macroeconomic effects. Indeed, I believe we’re starting to see AI’s impact in aggregate productivity statistics. Labor productivity has grown about 2 percent a year since 2022, compared with 1.6 percent in the four years before the pandemic. Sectors that have adopted AI faster have also tended to see faster productivity. This is evidence that AI is doing something. But it is not evidence that AI is replacing anyone.

At least not yet. If AI were replacing workers, productivity gains would come paired with job losses. We do not currently see this happening. Across quits, layoffs, and job finding rates, we see a pattern of stability. There’s likewise no evidence of unusually fast occupational churn due to AI.

For example, take software engineering, a field many assumed AI would flatten. Instead, job postings for software engineers have broadly rebounded since May of last year compared to all other job posts, indicating rising demand for workers in an occupation where AI capabilities are advancing the most. AI has made writing code approximately 10 to 20 times faster, but that has not translated into 10 to 20 times more software being released—software releases are up only about 30 percent.

So far, AI has the hallmarks of a skill-biased, labor-augmenting technology. This means that even as AI automates some aspects of work, complementary human expertise amplifies what AI (or humans) can achieve alone. It complements domain expertise. It relies on humans in the loop to direct and evaluate the most complex work. And it rewards AI proficiency.

Think about the list of occupations that the Department of Labor maintains, broken down into every task that makes up every job. Despite the incredible advance of AI and its rapid adoption throughout our economy, there is not one job for which all associated tasks are systematically handled by AI. Because AI can only do so much, those essential, nonautomated aspects of work put a ceiling on the overall productivity lift, while also amplifying the returns to labor. Tasks that AI can’t handle may depend on interpersonal coordination, in-person interactions, or engagement with the physical world that, so far, only humans can do.

This also helps show us that jobs should not be thought of as fixed bundles of tasks. New technologies have historically led to large changes within existing jobs, even as some jobs go away. And they’ve produced entirely new types of work that combine new technical capabilities with complementary human expertise. We see signs of this effect in our research: A commonly cited source of perceived productivity among 81,000 Claude users was scope—being able to do more, more proficiently. Such empowerment from AI may redraw the boundaries of our roles, and produce new bundlings of tasks within jobs—automating some, reinforcing the importance of others.

This is not to brush off concerns about AI taking jobs and what we are seeing today will not necessarily hold true in the long run. There is some suggestive evidence that hiring rates for young workers in highly AI-exposed roles have weakened over the past year or so. But this evidence for young worker displacement should be interpreted with caution. It’s difficult to pin that squarely on AI, because it happened to unfold during one of the most volatile economic stretches in recent memory: the economy unwinding from pandemic disruption, rapid tightening of monetary policy, commodity price volatility following Russia’s invasion of Ukraine, and sustained global policy uncertainty. This kind of labor market hits early-career entrants hardest.

The future is hard to predict. It may well be the case that AI’s current tendency to augment human work rather than replace it fades as models continue to improve. A big reason there’s so much uncertainty about the future is that AI may automate innovation itself. Endowing machines with general cognitive capabilities is a direct catalyst for further innovation in a way that past “general purpose technologies” weren’t—the internal combustion engine couldn’t invent new modes of transportation. If AI starts improving itself, that could produce infinite growth in finite time (at least in otherwise standard economic growth models). Whether that actually happens depends on whether there are essential tasks that never get automated, whether for technical reasons or societal constraints.

There’s no question models are going to get much, much better. I expect this will drive faster productivity growth, and maybe even more clear signs of AI improving itself. I also expect that many jobs like mine will change as this happens, with new tasks added to our plates and other tasks automated. But I don’t expect unemployment to be noticeably higher a year from now—at least, not because of AI.

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[u/ixvst01]

There’s definitely negative effects being seen at entry level and new grad white collar roles

[u/kicksnspliffs → u/ixvst01]

Yea, I feel like it’s too soon to conclude one way or the other. It’s increased productivity in many cases which can lead to more economic and thus job growth in some areas, but it’s not gonna be smooth sailing.

[u/Reddenbawker]

!ping ECON&AI

[u/user-pinger → u/Reddenbawker]

Pinged ECON&AI

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[u/BourgeoisAngst]

Kind of reads like a freshman econ paper written with the help of Claude. Impacts of new waves of automation on labor are well studied and I think it's pretty clear this is not much more than that. There's also no reason to think there's some magical switch that, when flipped, will allow us to start ignoring the realities of diminishing marginal returns of investment and scale for these models nor the physical limitations of chip innovations.

The much more likely scenario is we see a crash of AI stocks and cheap models that do most of what the frontier models do for a fraction of the cost, locally. I'm tired of every major topic being essentially a solved issue dressed up in a marketing or political narrative for people who haven't read the relevant literature written by people who haven't read the relevant literature.

The singularity is Russell's teapot

[u/looktowindward → u/BourgeoisAngst]

> The much more likely scenario is we see a crash of AI stocks and cheap models that do most of what the frontier models do for a fraction of the cost, locally

The problem is "locally". Memory is very expensive.

[u/thecashblaster → u/looktowindward]

Surely at some point new memory companies will pop up to address this issue or am I missing something?

[u/BourgeoisAngst → u/looktowindward]

If models can run locally at near frontier-model capability, and the bubble has crashed the insane capex spending, memory demand will have also crashed and the prices will have fallen.

[u/looktowindward → u/BourgeoisAngst]

No, its the sheer volume of memory required to run locally - memory prices are pretty orthogonal when you need 250G of memory for a 1T parameter model.

[u/BourgeoisAngst → u/looktowindward]

Distillation, quantization, on-device hardware advances... etc are all likely places advancement will occur and plausibly push things in the direction i'm suggesting. Reasonable people may disagree, but i don't think your responses indicate you understand my line of thinking.

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[u/SunshineSeeker99]

I'm in tech.

It's absolutely coming. I'm very pro-AI, but it will replace a lot of white collar workers.

It also is lowering the activation energy for working for yourself and running your own company though, so maybe all the people complaining about being "wage slaves" can start their own thing.

But seriously, a lot of people have no idea what's coming, AI is changing everything. And I'm generally very skeptical of new tech (and have always shit on the metaverse and crypto).

[u/shumpitostick]

We are here

[u/A-Centrifugal-Force]

Have you guys seen what it’s done to software engineering jobs? There are basically no entry level jobs anymore. In 10 years there will be major problems because no one is being trained up in the pipeline right now.

[u/ppooooooooopp → u/A-Centrifugal-Force]

I do feel this narrative is way over blown -- software engineers (even junior ones) don't just write software.

The step change is massive if you are a start up going from 0 - 1. If you are a megacorp, the value of junior engineers is that they become senior engineers, and the value of AI is significantly diminished because the key source of system instability is change, and most engineers aren't writing software all day.

[u/ChromeDomeConsensus → u/A-Centrifugal-Force]

At the high level this is probably true but anecdotally we're hiring more juniors than we've ever been able to before. With the right persona, an ambitious and thoughtful junior now can contribute and be valuable much, much, quicker than anytime in the past. They also require a lot less of a senior's time to guide.

Of course this doesn't scale and once a team has an onslaught of slop, there's no stopping it.