This makes sense given both automation and the US's role in the global economy, but it runs somewhat contrary to standard ideas of class and inequality.
Apparently "top executive" median pay is $105,350 per year: https://www.bls.gov/ooh/management/top-executives.htm
Now just think of the comp levels in sectors like government, education, etc.
If you click the link it mentions "general and operations managers". They're tossing a lot of different roles into the category.
It's the combination of tech and big or fast growing companies.
People who operate in FAANG or Silicon Valley bubbles (or who spend too much time on Blind) can lose track of what salaries look like in the rest of the world.
I often share Buffer's open salary page because their compensation is actually pretty normal from all of the data I've seen and hiring I've done: https://buffer.com/salaries
Every time it gets posted there are comments from people aghast that the software engineers "only" make $200K and in disbelief that the CEO's salary is "only" $300K.
Chief Executives is actually a specific sub-category of it and is, obviously, much smaller.
Can you elaborate?
I think AI outcomes distribute to contexts where it is used, and produce a change in how we work, what work we take on. Competition takes care of taking those surpluses and investing them in new structure, which becomes load bearing and we can't do without it anymore.
In the end it looks like we are treading water, just like it was when computers got 1M times faster in a couple of decades, but we felt very little improvement in earnings or reduction in work.
Surplus becomes structure and the changed structure is something you can't function without. Like the cell and mitochondrion, after they merged they can't be apart, can't pay their costs individually anymore. Surplus is absorbed into the baseline cost.
For a business, the question is whether you can make more money by doing more ambitious things.
The natural state of a capitalist system is the monopoly.
But given that the stock market hasn't panicked, this must mean at least one of these premises is false:
1. Economic activity is relatively flat.
2. AI makes us a million billion zillion times more productive than we used to be.
3. The stock market is rooted in reality.
This was already obvious, the more important question is what are we (collectively, society & our governments) going to do about it?
We (should have) already known most of our jobs were bullshit jobs, especially white collar jobs. The difference is now we might have something coming that will eliminate the bullshit jobs.
But society will always need bullshit jobs or the whole system collapses. Not everyone can go dig ditches, so what do we do?
I think this is a very important point. The hedonic treadmill means real gains are discounted. The novelty information cycle is like an Osborn Effect for improvements, like the semi-annual Popular Mechanic's flying car covers where there is an enticing future perpetually nearly here and at the same time disappointingly never materialized.
Agriculture is a good example of that: http://www.johnhearfield.com/History/Breadt.htm
This time the jobs most in the crosshairs of AI are the jobs that constituted the paper pushing overhead of modern society, all the paper pushing jobs. Instead of $1 widgets from China replacing $2 domestic widgets it's gonna be $1 AI services replacing $2 services that require a real human.
This is hard to reason about because people tend to consume these kinds of services in big multi hundred or multi thousand dollar increments but in practice what it means is that when you have to engage an accountant, engineer, having something planned out in accordance with some standard, that will be substantially cheaper because of the reduced professional labor component.
And of course, as usual, the string pulling and in investor class will get fabulously wealthy along the way.
Does the work you do provide more or less value to the company than your salary? Where does the difference go? If your killer feature closes a $5M deal, who gets that money?
We live as capitalist serfs. Someone else gets all the value you create, and you should be grateful for the peanuts they toss back to you.
The 1% pockets, this is where the vast majority of the extra productivity computers/internet/automation brought goes to for the last 50 years: https://www.epi.org/productivity-pay-gap/
1) The salaries of corporate employees 2) Shareholders and capital owners
Regarding number 2: "Shareholders" would include anyone who owns any stock at all, including a lot of middle class people with a simple S&P 500 ETF in their portfolio.
And the increase in productivity allowed more people to become capital owners, AKA entrepreneurs. The explosion in software entrepreneurs, for example.
Yes, but shares are not at all uniformly distributed. Tim Cook owns 3.28 million shares of AAPL. For comparison, the 50 million Vanguard customers have to divide 1.3 billion shares amongst them, averaging about 26 shares of AAPL each.
> And the increase in productivity allowed more people to become capital owners, AKA entrepreneurs. The explosion in software entrepreneurs, for example.
The majority of those end up getting bought by larger software companies.
Overall capital ownership is increasingly concentrated among a small number of elites.
Because no matter what fairy tales you want to believe in your $20 "invested" in palantir won't make you a "shareholder" lmao
(don't forget to "allow pasting" in [chrome] console first)
A lot more inconvenient for others to have to pick colors that satisfy all potential sight issues, which is primarily why I think it should be an OS solution rather than an individual creator's responsibility. It's not that I don't care about those with the sight issue, it's purely about who is responsible for creating a reasonable solution. And honestly, there's no way every creator is going to study accessibility and so it's just a never ending uphill battle. If you had a tool in your system already that could help, why wouldn't you use it?
1) Avoid contrasting red/green and blue/yellow, as these are common colorblind pairs.
2) Pick shades that still look different when shown in grayscale.
3) All bar charts should have 0 at one end.
4) Please no 3-D pie charts.
To find good color palettes, check out https://colorbrewer2.org
I generally am against people who have expectations of how they want others to communicate. Be it colors, pronouns, whatever- you’re just setting yourself up for disappointment and it’s not out of malice so just move on or find your own way to deal with what people are putting out there.
https://www.vischeck.com/run.html
It twiddles colors in a physiologically-aware manner to improve legibility for colorblind observers:
https://github.com/wadelab/VischeckTinyeyes/blob/main/websit...
BLS forward looking guidance means nothing when technology revolutionizes the nature of work.
No one can predict everything perfectly. This is just the guidance based on the data that was reported. AI is advancing faster than anyone can imagine and no one knows the impact - good or bad.
Putting aside the slop facade place atop the data....why would we trust the data?
Yay!
>Computer Programmers: -6%
Oh no
(Source: https://www.bls.gov/ooh/computer-and-information-technology/...)
Computer Programmers median pay according to BLS: $98,670 per year
(Source: https://www.bls.gov/ooh/computer-and-information-technology/...)
Software developers typically do the following:
- Analyze users’ needs and then design and develop software to meet those needs Recommend software upgrades for customers’ existing programs and systems Design each piece of an application or system and plan how the pieces will work together
- Create a variety of models and diagrams showing programmers the software code needed for an application
- Ensure that a program continues to function normally through software maintenance and testing
- Document every aspect of an application or system as a reference for future maintenance and upgrades
(Source: https://www.bls.gov/ooh/computer-and-information-technology/...)
Computer programmers typically do the following:
- Write programs in a variety of computer languages, such as C++ and Java
- Update and expand existing programs
- Test programs for errors and fix the faulty lines of computer code
- Create, modify, and test code or scripts in software that simplifies development
(Source: https://www.bls.gov/ooh/computer-and-information-technology/...)
Programmers is like a translator; somebody else came up with what to do and you're doing the mechanical work of converting words into C++.
Developer involves coming up with what to do.
Hence programmers is a lower paid position.
It feels like the intent was that "Programmers" were the ones doing the routine / lower skill tasks while the Developers were the ones that did the specification and architecture.
Those got juggled around and largely people getting listed as "Computer Programmer" is going down as the company relists them as Software Developer.
This is also part of the confusion of "Web Developer" which is also in there.
It reflects what government thought management thought title and roles were some years ago.
---
Edit: From days of old: https://web.archive.org/web/20110616142157/https://www.bls.g...
15-1132 Software Developers, Applications
Develop, create, and modify general computer applications software or specialized utility programs. Analyze user needs and develop software solutions. Design software or customize software for client use with the aim of optimizing operational efficiency. May analyze and design databases within an application area, working individually or coordinating database development as part of a team. May supervise computer programmers.
15-1133 Software Developers, Systems Software
Research, design, develop, and test operating systems-level software, compilers, and network distribution software for medical, industrial, military, communications, aerospace, business, scientific, and general computing applications. Set operational specifications and formulate and analyze software requirements. May design embedded systems software. Apply principles and techniques of computer science, engineering, and mathematical analysis.
15-1131 Computer Programmers
Create, modify, and test the code, forms, and script that allow computer applications to run. Work from specifications drawn up by software developers or other individuals. May assist software developers by analyzing user needs and designing software solutions. May develop and write computer programs to store, locate, and retrieve specific documents, data, and information.
... And for completness
https://web.archive.org/web/20130624010204/http://www.bls.go...
15-1134 Web Developers
Design, create, and modify Web sites. Analyze user needs to implement Web site content, graphics, performance, and capacity. May integrate Web sites with other computer applications. May convert written, graphic, audio, and video components to compatible Web formats by using software designed to facilitate the creation of Web and multimedia content. Excludes "Multimedia Artists and Animators" (27-1014).Reason for hope
They're saying that programmers will be declining. While Developers, and crucially, Testers and QA people will be increasing. That testers and QA become more important in the future sounds plausible to me in a future hypothetical world of ubiquitous AI.
All of that doesn't necessarily imply that the Developer class of employees will grow at the same rate as the Tester and QA classes of employees.
My friends and I who have a bachelor's degree in CS make more money than my friends who have or are working towards master's degrees in CS, because the former are working in the private sector and the latter are in academia making peanuts.
Edit: Another possible reason that Masters degrees were less common in the past, so the Bachelors pay statistics skew towards people with more work experience in their higher earning years, whereas the Masters pay statistics skew towards younger people with less work experience.
Congress/president should pause H1B visas or hike up fee to 200-500K so that only truly exceptional talent are allowed in. Right now it's just give away to corporations that are laying off people by tens of thousands.
1) how many of these people leave the country in this analysis.
2) OPTs likely will get h1b/l1s/leave the country and are being counted distinctly.
3) not all h1b/l1/OPTs are for tech. majority for sure, but there's a conversation factor.
specially in the current situation that green cards are much harder to obtain and many OPTs don't find a job, I expect 1 to be much larger than in the past.
as a more general observation, this line of reasoning does fit lump of labor fallacies: https://en.wikipedia.org/wiki/Lump_of_labour_fallacy
Since the fee went up to $100k, I’m not aware of any companies still sponsoring hires who need a new H1B
We will see how much the $100k fee affects things during this H1B lottery round in few weeks.
A 100k one-time fee is nothing for big employers. That's 25k/year for 4 years, and if you realize that H1B's can't easily leave their job it's obviously worth it.
Compare hiring an H1B that is stuck at their job, to an American who can leave at any time. You can pay the H1B a lower wage to compensate for the fee you paid to get them into the role. 25k/year for 4 years is worth it for not only the reduced churn that comes with training a new person, but also you don't have to pay any of the incentives that come with getting a new employee into the role like sign-on bonuses, wage bumps, benefits etc.
https://apnews.com/article/teacher-jobs-h1b-j1-visa-online-s...
Like many school systems facing teacher shortages, South Carolina’s Allendale County has looked overseas for help. A quarter of the teachers in the rural, high-poverty district come from other countries.
The superintendent praises the international educators — mostly from Jamaica and the Philippines — for their skill and dedication, but she is preparing to lose some of them as the Trump administration reshapes visa programs.
Facing higher visa sponsorship costs and uncertain immigration policies, Superintendent Vallerie Cave said it feels too risky to extend some international teachers whose contracts are up or bring on others.So healthcare industries turn to H1Bs to hire specialty positions in underserved / rural areas. The alternative is to shut these facilities down, which has other negative aspects to communities.
It turns out that they are, but (if I do not misread the situation) there is a regulatory bottleneck:
>The United States is grappling with a physician shortage, but the solution does not lie in simply opening more medical schools. As a physician-scientist and former founding dean of a medical school, I argue that the true bottleneck is not the number of medical school graduates but the insufficient number of residency training positions. Since the Balanced Budget Act of 1997, which froze the number of Medicare-funded residency slots, the United States has seen a steady increase in medical graduates, yet the availability of residency spots has stagnated. This mismatch between undergraduate medical education (UME) expansion and the lack of corresponding growth in graduate medical education (GME) is the key issue.
https://pmc.ncbi.nlm.nih.gov/articles/PMC12256077/
As this has been the arrangement since 1997, by now a graduated American child of an immigrant H1B specialist trained in a foreign country may be unable to secure a 'residency training position' and therefore unable to practice medicine in his or her own country? It sounds absurd.
I find this argument extremely funny because when immigrations are taking the white collar jobs, you guys get anti immigrants, tighten the visa stuff, but when blue collar and low level jobs are taken by illegal folks you turn and blind eye and noone is illegal in stolen land login.
I 100% agree that H1B has been extremely abused by folks from specific country running body shop tech consultancies but the solution is not to hike up the fees to 200k-500k.
The 100k fee by Trump admin is already showing effects in the job market. Most companies are not readily sponsoring H1B visa anymore, getting a big tech job as a intl student is already tough and only exceptional ones are getting such jobs.
Meanwhile, the people in tech who oppose immigration often do bring up the same argument you do - that it's bad to allow immigrants to compete with blue collar American citizen labor even if this competition would make some things that these white-collar tech workers buy cheaper - or ground their opposition to immigration in negative effects of immigrants on American society that aren't directly related to competition for blue-collar jobs (generally, that the presence of large numbers of immigrants has bad cultural or political consequences for the US as a whole).
The political fight over immigration among white-collar tech workers I think has more to do with battling moral claims, or different visions of what the US should look like culturally and politically, than it does over purely-materialist job competition concerns that they are hypocrites about when the job competition is happening to blue-collar workers.
There's lies, damned lies, and then: there's statistics.
You have to counter the growth in jobs based on how many new people there are to take them, the location in which they are, and somewhat weirdly other jobs.
Plenty of people feel so dejected at the current state of things that they leave computer work entirely making "openings" where there isn't actually any growth.
Like all things that you try to understand: a single datapoint, when averaged, is like trying to calculate the heat from the sun by looking through a telescope at jupiter. It will give you a far-out tiny facet of data that only makes sense when coalesced with a hundred other ones.
On second thought, client service folks might do extremely well here!
What you mention here is the exact thing why my earlier relationship went bust, because I didnt have any of these, then the children arrived :-X
In the AI maximalist world where humans are obsolete and cannot contribute to the economy in any meaningful way, there is actually no reason for public education to exist beyond being a free day care for non-rich people. Why learn algebra/calculus at all if the AIs can do it? Why should the US invest billions of dollars into public education instead of data centers?
I hope the US and AI leaders are still "speciesist" in that they put humans first. I hope AI will cure all illnesses, unlock space travel, and lead to flourishing of humanity, not just a flourishing of datacenters. It's also possible that AI just cleave societies in half and we are all worse off for it.
Stand in front with a gun while mobs come to burn down the data center that took their jobs.
(I think I'm half joking).
I doubt it'd be old hit-and-run, more like small scale Ukraine with drones filled with explosives.
Apple, a very successful company, makes 300B/y revenue? (ish)
~10% is all you need to be Apple.
And, it can work by taking all of 10% of the jobs and collecting the whole salary (the AI employee -- dubious proposition),
or by taking 10% of everyone's salary and automating part of everyone's job (the AI "tool" -- much more plausible).
If "part" being automated is >10%, we all win in the long run, every company gets productivity growth without cost growth, etc etc.
If you add in data center costs, and multiple competing AI companies, and then expand the TAM to all white collar work worldwide, you can make everyone successful beyond their wildest dreams with a "20% of work for 20% of the cost" model. Again, how you distribute that 20% remains to be seen (20% new unemployment, or new 0% unemployment with "tools".
I formalized my thoughts here: https://jodavaho.io/posts/ai-jobpocolypse.html
Potable water is far more important than AI or iPads ever will be, but the world's most valuable water company only does about 5B/year in revenue: https://en.wikipedia.org/wiki/American_Water_Works
In the same way that Amazon gets rich taking ElasticSearch for free and charging for hosting, Amazon will take free models and charge to host them. The companies building frontier models have massive R&D costs and no moat.
It's also understated, because the real value of AI is not in replacing work, but making new products possible either because it's finally cheap enough to make them, or because -- AI.
So no, little or none of the AI productivity gains will go to workers, barring significant changes in public policy like universal basic income and the massive tax increases necessary to implement it.
Do the productivity gains from stack overflow "belong" to the workers? Do the productivity gains from better google search or wikipedia? If I want to charge by the product instead of hour - I can leave and start consulting or contracting.
How should those productivity gains go to employees? I own equity in this company, and most others I have formerly worked for. I have free access to public equity markets, tax subsidized 401k and IRA plans which have historically enriched 100s of millions.
I've been through layoffs where I didn't have to take a day of reduced salary or unemployment because of severances nor did I experience a single day of health care coverage lapse b/c of same, or b/c of spouse's insurance or public marketplace.
My situation is not unique to software engineers in the USA. The public market, cheap/subsidized retirement plans + equity bonuses have effectively seized a good portion of the means of production for the workers, allowing consistent enrichment from expansion of industry. And corporate america for all it's evils has produced the entirety of the social safety net that I've used after I graduated, and that is while changing jobs basically whenever I wanted (plus one time I didn't)
Guys, I don't see it yet. Maybe I'm dumb, but it's not here yet and there is a case to be optimistic that everyone is ignoring. Prepare for the worst, but once prepared, banish it from your mind.
Given the state of AI (LLMs) - they still need a very human (skilled driver) to operate
Frequently seen as a big fun number in pitch decks. "The TAM for our new Coca-Cola killer is $1.6T: all humans who imbibe liquids on a regular basis. You simply MUST invest."
> Rate the occupation's overall AI Exposure on a scale from 0 to 10.
Are LLMs good at scoring? In my experience, using an LLM for scoring things usually produces arbitrary results. I'm surprised to see Karpathy employ it
Now I'm not sure if this is actually an LLM only thing. Because I think people probably do similar when you ask them to give a number to things without providing a concrete grading rubric...
Started my career in the decade of offshoring and didn't think we'd have anything close to an "AI" taking our jobs before we potentially unionized or had a government that would protect its labor force from being replaced by literal robots.
2020-2022 felt like the usa tech ship was finally growing into something really great. All gone now.
When I worked in devops I always worried that my job was automating away other engineers, it definitely had a "when will this come for me" feeling, because it really was, now the dev and ops are both getting automated away.
This is my first time looking at HN in practically a year. Tech is just so uninteresting to me now. Nobody is hiring SDE/SWE/SREs except for the problem makers, like Anthropic, Meta, etc. Anthropic has pages and pages of $300k-$600k roles open right now. But do you go help the rest of your colleagues lose their jobs?
I guess lets talk about kubernetes or something...
If you turn on the color filters in accessibility settings in macOS you can see what the contrast could look like to a colorblind person.
Ask a colorblind person to explain how to win at candy crush and you'll be surprised (hint: we do not use colors, we use the shapes).
The general trick is you can rely on differences in color lightness, patterns, text and icons, but not differences in color hue. The page should be usable in grayscale.
Whats the outlook like?
Thank you!
Some argue more apps means more plumbers and problem solvers, but we'll see.
Speculation: I think infra roles including on-prem are growing again, based on things I've seen.
Needs
- [utility] add filter by keyword / substring match, e.g majority of visualized reports are un-labeled requiring hovering with a mouse pointer
- [improve discovery] add sort by demographic / pop impact, e.g largest block is 7m ('Hand laborers and movers') and default sorted to bottom-left
A -4.0% hit to cashiers may have less of an impact than -4.0% to lawyers or another category that is propping up the middle of the economy with spending.
deep down you all know something is just going to randomly get released one week in the near future that makes you go "well pack it up boys", or you just haven't been paying attention
to clarify - just like the site says - I don't think those jobs are going away, maybe entry level will have the same issues as some industries are encountering, but ideas of relative immunity are completely wrong
I'd like to use this on my website and also see if I can create variations for some of the major EU markets.
> Taxi Drivers, Shuttle Drivers, and Chauffeurs
> Overall employment of taxi drivers, shuttle drivers, and chauffeurs is projected to grow 9 percent from 2024 to 2034, much faster than the average for all occupations.
...word?
https://apnews.com/article/trump-jobs-firing-f00e9bf96d01105...
All the "research" on the site comes from a single LLM prompt.
And for whatever reason a lot of people in startup/tech seem to have a huge Dunning-Kruger effect blind spot where they believe knowing a lot about one thing makes them an expert in everything.
This used to just be funny, but when it started to intersect with politics it began to actively contribute to destroying society. It isn't funny anymore.
(I don't think Karpathy's job data here is destroying society, this is a more generalized observation).
There is definitely impact on Software engineering jobs at the moment, interns/juniors are struggling to find jobs, companies are squeezing every bit of dev slack time to produce more stuff with AI.
Is that notion supported by this content? The BLS Outlook for most software engineering jobs is most in the "much faster than average" growth range.
* Yes software engineering jobs can grow - by increasing demand for custom software thanks to coding agents unlock
* AI can impact it - by making software engineers LLM code approvers
What would be useful is tracking the change in minimum pay per hour from legitimate job listings, now that there are quite a few states that require posting pay ranges on job listings.
I guess that was to be expected...
> Rate the occupation's overall AI Exposure on a scale from 0 to 10.
The sad part isn't that this is low-effort AI slop, but that intelligent people and policy makers are going to see it and probably make important decisions impacting themselves and others based on these numbers.
In addition, little work is done to separate the classes. He has probation officers in the same node as teachers, completely separate from law enforcement.
Here's some much better examples:
- https://www.washingtonpost.com/nation/2022/05/04/abortion-nu...
- https://flowingdata.com/2015/04/02/how-we-spend-our-money-a-...
It's not great for them, but it's a definite advantage for people who are already in the mindset of distinguishing and discriminating information and sources on merit, instead of running an "AI bad" rubric as part of their filter.
AI has already won. It's taking over. It might be a year or two, or five, or ten, but AI isn't slowing down, nobody is going to pause, and there's a whole shit ton of work people do that won't be meaningful or economically relevant in the very near term. Jevons paradox isn't relevant to cognitive surplus - you need a very different model to capture what's going to happen.
It's time to surf or drown, because it doesn't look like any of the people in charge have the slightest clue about how to handle what's coming.
Maybe it was linked from a comment somewhere on HN but just today I saw a post saying “Microwaves are the future of all food: if you don’t think so, you better get out of the kitchen”
Microwaves have already won. There will be a microwave in every home over the next few years.
It’s time to start microwave cooking or drown
It's annoying that the dishes still have some pooled water in them when the cycle finishes; it doesn't always get everything perfectly clean; I have to know not to put the knives or the wooden stuff or anything fancy in it. But in spite of all of that, I use it every day, it's a huge productivity boost, and I'd hate to be without it.
Fridge OTOH, not so much.
Microwaves do one thing, but they do it reliably. Microwaves didn't affect the culinary industry because cooking is far more than just heating food, and many tasks are very difficult to automate. LLMs are more general-purpose - the average Joe is now relying on them as a source of truth, advice and mental work across the board. However, LLMs can't be guaranteed to always be reliable, it's all probabilistic. The threat of automation here is in taking away a lot of the less important or less complex work. Low impact + high precision (microwave) vs. high impact + low precision (AI)
LLMs require a lot more effort.
This is an incredible self-report. If you consider microwaved meals to be your default method of cooking and not something primarily for reheating leftovers or defrosting frozen meat, I sincerely hope you've gotten your cholesterol and blood pressure checked recently. That is not normal.
I’m from northern Europe. I might use the micro to heat up leftovers or a cup of water for tea or whatever in a pinch, but in this household (and at all my friends’), the stove and the oven cooks the food. I know literally no-one who could say they cook most meals in the micro.
I didn’t have a microwave oven before we bought a house. It took up too much space to justify, for such a relatively rarely-used appliance.
Thankfully there is real data if we want to know how microwaves are used. Survey below says they are used a bit more than ovens, but half as much as cooktops/stoves. Varies by cohort and meal.
Source: https://indoor.lbl.gov/publications/residential-cooking-beha...
Although, the analogy seems sort of useless, in that the food preparation ecosystem is really not any less complex than the program creation ecosystem, so it doesn’t offer any simplification.
Ovens are a special occasion thing in my house because our oven is huge and I can usually do the same thing in the air fryer, which is just a small convection oven.
Not true in my household, in my parent's, in my in-laws, or any of my closest friends'. And none of us are cooks, so it's not a niche thing.
I'm sure in a lot of households the microwave oven is the primary form of cooking, but it's important to look outside the bubble before reporting trends.
That really only makes sense if for households with a toaster oven, single adults, childless couples, and retired people. A toaster oven makes a lot more sense for small meals, in part because it can heat up much faster than a full oven.
Otherwise, a daily family meal isn't a special occasion.
You think "there's a whole shit ton of work people do that won't be meaningful or economically relevant in the very near term" is wrong?
No, AI has not "already" won. And phrasing it as you do, "It's taking over. It might be a year or two, or five, or ten" is an admission of that.
People may indeed not pause, but there's never any guarantee that the next step of progress is possible; whatever we reach may be all we can do, and we'll only find out when we get there. Or it might go hyperbolic and give us everything.
I'm not certain, but I suspect Jevons paradox is probably the wrong thing to bring up here, that's about cheaper stuff revealing more latent demand, and sure, that's possible and it may reveal a latent demand for everyone to build their own 1:1 scale model of the USS Enterprise (any of them) as a personal home, but we may also find that AI ends the economic incentives for consumerism which in turn remove a big driver to constantly have more stuff and demand goes down to something closer to a home being a living yurt made out of genetically modified photovoltaic vines that also give us unlimited free food.
(I mean, if we're talking about the AI future, why not push it?)
What I do think is worth bringing up is comparative advantage: Again, this is just an "I think", I'm absolutely not certain here, but if AI can supply all demand at unlimited volumes*, I think the assumptions behind comparative advantage, break.
> It's time to surf or drown, because it doesn't look like any of the people in charge have the slightest clue about how to handle what's coming.
Yes, and I think they've also not even managed to figure out the internet yet.
* and AI may well be able to, even if all models collectively "only" reach the equivalent of a fully-rounded human of IQ 115; and yes I know IQ tests are dodgy, but we all know what they approximate, by "fully rounded" I mean that thing their steel-man form tries to approach, not test passing itself which would have the AI already beat that IQ score despite struggling with handling plates in a dishwasher.
OP comment is not clever
Ah, the classic, forever-untestable "it's just around the corner" hypothesis.
I've lived through multiple "it's gonna be over in 12-18 months" arguments since November 2022. It's a truism for any technology to say that it's going to get better over time. But if you're convinced that "AI has already won", why not make a specific prediction? What jobs are going to be obsolete by when?
Jevons paradox was never relevant to cognitive surplus. That isn't what it's about.
Cognitive surplus only strengthens Jevons paradox. Humans are a competitive advantage for businesses in a world dominated by human needs
1. Brick and mortar is dead.
2. The internet will die.
3. What is the business model? (this one still seems to exist to this day to some extent, lol)
Reality fell between 1 and 2.
just because it was wrong once doesn't mean its never wrong. And was it really that wrong? The internet is great but would it be the worst thing in the world if we didn't live our lives around it?
You'd probably put me into that bucket, although I'd disagree. I'm not at all against using AI to do something like: type up a high level summary of a product featureset for an executive that doesn't require deep technical accuracy.
What I AM against is: "summarize these million datapoints and into an output I can consume".
Why? Because the number of times I've already witnessed in the last year: someone using AI to build out their QBR deck or financial forecast, only to find out the AI completely hallucinated the numbers - makes my brain break. If I can't trust it to build an accurate graph of hard numbers without literally double checking all of its work, why would I bother in the first place?
In the same way, if you tell me you've got this amazing dataset that AI has built for you, my first thought is: I trust that about as much as the Iraqi Information Minister, because I've seen first hand the garbage output from supposedly the best AI platforms in the world.
*And to be clear: I absolutely think businesses across the board are replacing people with AI, and they can do so. And I also think it'll take 18+ months for someone to start asking questions only for them to figure out they've been directing the future of their company on garbage numbers that don't reflect reality.
If I were in need of hard analytics you can be damn sure I'd have it build a tool with a solid suite of tests following a rigorous process to ensure the outputs are sound. That's the difference between engineering and vibing.
I think LLMs are the equivalent of someone with a PhD in English literature and a few other things, and can be very intelligent and literate without being particularly good with numbers.
On the other hand you have plenty of machine learning numbers that are absolute beasts at everything number-related. I'm assuming you wouldn't put George RR Martin in charge of building your datasets.
I think AI is not going anywhere.
I also don't think the future will play out as you envision. AI is a very poor replacement for humans.
And I say this as a misanthrope who doesn't have a particular beef against AI.
Published AI generated code is a mild negative signal for quality, but certainly not a fatal one.
Published AI generated English writing is worthless and should be automatically ignored.
I could understand if all the naysayers doing old fashioned stuff like work all of a sudden have no more work to do. But the AI Embracers will have what, in comparison? Five years of experience manipulating large language models that are smarter than them by a thousand fold?
Could you elaborate on this? Is it just a claim, or is there some consensus out there based on something that it doesn't/shouldn't apply?
So... What exactly are you talking about?
Whether people are adopting AI or not, everybody doing the same kind of job gets the same number for exposure to AI.
You can claim that AI is creating a Jevons paradox situation and making companies hire as crazy the people it nominally replaces. But then you would have to point any instance of that happening, because it's clearly not there either.
a. "Has already won"
b. "Might be a year or two, or five, or ten"
I use AI every day as part of my work, it's very unclear to me where it's going and we have no idea if we're on an exponent or S-curve. Now, normally people talk with conviction because they have more data. But one of the breakthroughs of crypto was this social convention of just have very strong opinions based on nothing. A lot of that culture has come over to AI.
Your comment typifies this, it's all about I need to get on board, AI has already won, you've got an advantage over me because you realise this.
Go back, look at the actual article you're commenting on. Did the AI analysis of job exposure provide anything of value. I'm not totally convinced it did, and you didn't even think about it. What critical thinking did you do about the data that came out of this dashboard.
This cuts both ways...
> there's a whole shit ton of work people do that won't be meaningful or economically relevant in the very near term
What work do you think AI is going to replace? There are whole categories of people who are going to drown in the hubris of "AI being able to do the job" when it cant.
The moment one stops pretending that its going to be AI, that were getting AGI and views it as another tool the perspective changes. Strip away the hype and there is a LOT there... The walls of the garden are gonna get ripped down (Agents force the web open, and create security issues). They end lots of dark patterns, you cant make your crappy service hard to cancel... because an agent is more persistent to that. One size fits all software is going to face a reckoning (how many things are jammed into sales force sideways... that dont have to be). These things are existential threats to how our industry is TODAY, and no one seems to be talking about the impact to existing business models when the overhead of building software gets cut in half (and how it leads to more software not less).
However I was completely unimpressed with this tool when I saw it this weekend for two reasons:
The first is directly related to how this is built:
> These are rough LLM estimates, not rigorous predictions.
This visualization is neat (well except for reason number two), but it's pretty much just AI slop repackaged. There's no substance behind any of these predictions. Now I'm perfectly open to the critique that normal BLS predictions are also potentially slop, but I don't see how this is particularly valuable.
And the second, like 8% of male population I'm colorblind, so I can't read this chart.
For the record, I do agentic coding pretty much everyday, have shipped AI products, done work in AI research, etc.
Ironically, it's comments like yours that keep me the most skeptical. The fact that an attack on a strawman is the top comment really makes me feel like there is some sort of true mania here that I might even be a bit caught up in.
Over the past year (where Opus has supposedly changed the game), we're seeing ~10% more job postings for software developers compared to this time last year [1,2]
A huge amount of our work is not easily verifiable, therefore it's extremely hard to actually train an LLM to be better at it. It doesn't magically get better across the board.
AI HAS WON. SURF OR DROWN. YOU DONT KNOW WHATS COMING!!!?!?!
Stop with this doomer drivel. It's sick. It's not based in reality and all it does is stress innocent people out for no reason.
AI is great for searching. I ll give you that. And that itself is a big deal. In software development, there is also real value provided by AI if you use it for code reviews. But I am not sure how much worth it would be if you have to retrain a model with new information just to give better search results and for code reviews..
Maybe that will be subsidized by all the people like you who want everything to be done by AI, for the rest of us to use it as a better search tool and use it for quick reviews..who knows!
brainbroken by chatbots lmao
Man.. I suggest you touch some grass. You are living in a bubble.
Companies Are Laying Off Workers Because of AI’s Potential - Not Its Performance - https://news.ycombinator.com/item?id=47401368 - March 2026
> Some companies that announced large headcount reductions because of AI have since revised their talent strategies or have faced public criticism. Klarna, for example, the Swedish fintech that offers “buy now, pay later” e-commerce loans, reduced its human workforce by 40% between December 2022 and December 2024 as it invested in AI. (The company used a hiring freeze and natural attrition, not layoffs to achieve this cut.) But in 2025 the company’s CEO told Bloomberg that Klarna was reinvesting in human support, explaining that prioritizing lower costs had also led to “lower quality.” A spokesman told HBR that the company has hired about 20 people to deal with customer service cases the AI assistant can’t handle, and that the use of AI “changes the profile of the human agents you need in the customer support role.” The language-learning company Duolingo announced that AI would be used to replace many human contractors, and it faced considerable criticism on social media.
> For one, AI typically performs specific tasks and not entire jobs. As an example, Nobel laureate Geoffrey Hinton stated in 2016 that it was “completely obvious” that AI would outperform human radiologists within five years. A decade later, there is no evidence that a single radiologist has lost a job to AI—in part because radiologists perform many tasks other than reading scan images. Indeed, there is a substantial shortage of them.
The 'AI-Washing' of Job Cuts Is Corrosive and Confusing - https://news.ycombinator.com/item?id=47401499 - March 2026
* Companies are "AI washing" layoffs, blaming artificial intelligence for workforce reductions they would have made anyway, according to OpenAI CEO Sam Altman.
* A Resume.org survey found that 59% of hiring managers say they emphasize AI's role in layoffs because it "is viewed more favorably by stakeholders than saying layoffs or hiring freezes are driven by financial constraints".
* The stated reason for the layoff matters more than the fact of the layoff, and framing cuts as proactive restructuring around AI can result in a valuation boost, even if the technology doesn't actually work.
> The AI premium isn’t even reliable. By late 2025, Goldman Sachs group Inc. found that investors were actually punishing AI-attributed layoffs, with shares falling an average of 2%. The analysts concluded that investors simply didn’t believe the companies. But Block’s surge shows the incentive hasn’t vanished. It’s just a lottery instead of a sure thing. And executives keep buying tickets.
> The broader data confirms the gap between narrative and reality. A National Bureau of Economic Research study published in February surveyed thousands of C-suite executives across the US, UK, Germany and Australia. Almost 90% said AI had zero impact on employment over the past three years. Challenger, Gray & Christmas tracked 1.2 million layoffs in 2025, and AI was cited in fewer than 55,000 of them. That’s 4.5%. Plain old “market and economic conditions” accounted for four times as many.
So! Sophisticated capital market participants don't believe this; why do people here?
AI is making CEOs delusional [video] - https://www.youtube.com/watch?v=Q6nem-F8AG8
It's been several years and nothing has changed except the AI grift is crumbling as we get out of the post-covid slump.