AI is already too useful to discard, we could automate 90% bureaucracy and government jobs and no one would feel the difference. But of course fear/angst/rage sells.

I think a lot of it is actually the tech for a lot of reasons:

0. No one wants a datacenter in their backyard or hooked up to the grid while the electricity burden is carried by households. People are afraid of losing their property values and being unable to move away if a DC is built nearby - effectively being trapped there. People in Memphis are breathing in gas fumes from the XAI datacenter there. There are concerns about corrosion byproducts making its way into the aquifers from DC waste water. If DC construction takes the cheap option no sound insulation is installed and people can’t sleep and some even lose their hearing: https://www.usnews.com/news/national-news/articles/2026-04-2...

People are pissed that towns and cities are bypassing public approval to placate corporate builders.

1. People have been told to fear for their jobs

2. Many people believe labs have stolen vast amounts of intellectual property

3. Engineers are being pressured to use AI and told they “aren’t prompting right” if/when it doesn’t work for their use case

I can go on. But I actually think the majority of the backlash has nothing to do with stock valuations.

I think AI backlash has less to do with the tech itself and more with its broader impact on society in the current system, if it delivers a quarter of its promises. Those doing the backlashing feel that they are going to lose much more than they are going to gain.

This is often repeated but not true. Ed Zitron conflates the two all the time.

There's another "they took our jobs" group that doesn't fit into "AI is overhyped" or "AI is useless".

They see that AI is capable and fear it.

We software engineers have a different experience with AI than most other fields. We have vast arrays of guardrails in our field, with unit testing, CI/CD, source control being relatively easy since we mostly produce textual artifacts, strong typing, compilers with decades of experience in giving targeted error messages, all sorts of things [1]. When AI takes two steps forward and then does something stupid, we have so many guardrails that our harnesses can easily get the error message, feed it back in, and the AI can pick up the pieces and carry on. We hardly even notice this process.

If you watch an AI and dig into the details of everything it is doing, you can see it repeatedly banging into these guard rails. There's nothing wrong with that necessarily. As a human being, I bang into those guard rails all the time too. That's where they came from in the first place, to let humans bang into them. And we've built a lot of them.

However, in a lot of the rest of the world their experience with AI much more resembles that of the more critical voices that post here. A lawyer who uses an AI that makes two correct citations and then an incorrect one has many fewer automated guard rails to work with. It is relatively easy to imagine a system that at least verifies the citation exists (I've heard that's easier said than done due to the system depending on humans to resolve sloppy references but still it's feasible), but the task of deciding if the AI correctly used the citation, either in the abstract sense of it being correct or in the sense of it being the best way to use it to advance the current case, is a vastly harder decision than "ah, that change failed to compile, try again".

Accounting seems like another good example. Yes, it has the obvious guard rail of "do the books balance", but that's the beginning of accounting, not the end. It's difficult to put up guard rails for how the accounting is done from there. An accountant will experience an AI accountant as doing OK sometimes but making really dumb decisions that couldn't be caught by anything other than human review, and I have to imagine that the lack of learning and the way the AI will tend to make the same mistakes over and over must be incredibly aggravating.

I think there's probably more truth to "AI is useless" than we may see. I think a lot more people than we realize have had the experience of using AI a while, putting some trust in it, then having that trust grotesquely violated when it says something stupid in an email or makes boneheaded errors in a spreadsheet. We're maybe just now exiting the portion of the hype cycle where it is simply culturally unacceptable to criticize the AI and entering the part where it is culturally both acceptable and expected, and we software engineers may look on in bafflement at the other fields and their complaints because it's working for us, what's your problem?

[1]: https://jerf.org/iri/post/2026/programming_is_engineering/

[delayed]

That’s roughly it.

I don’t really have a use for it myself that I can’t solve some other way cheaper or easier without the damage and uncertainty it does.

I’m not really that impressed.

It seems by definition "below par" of whatever human activity it's training on. How can we achieve greater and greater heights of intelligence if we're just creeping closer and closer to a sub-par copy of human creative activity.

This applies to simplistic use of AI, or "one-shotting", the best are using it as raw material, not final product.

Check out the work of Zack London (AKA Gossip Goblin) on YouTube. It's objectively good - I don't even care what your opinion is.

How do you know it's being served at wildly below cost? AFAIK API pricing across the board is actually higher than what inference would cost? Yes there are subscription plans that subsidise tokens but they exist primarily to hook people in, so as to encourage their workplace to adopt it, whereby they then have to pay for an enterprise plan with zero subsidies like the subscription plans have. Training is very expensive, but you only do that once.

I predict costs will fall.

>The untold promise of [tractors] is to replace labor. [...] Mere tools would never justify this kind of investment.

How's this any different than say, tractors, or the mechanical loom? After all, agricultural employment went from 90% in the past to 1% today.

From TFA:

>The buildings summon a vitriol well beyond conventional nimbyism. More Americans say they would be happy with a nuclear reactor next door than a data centre. Even plans to build one in the Utah desert have met with passionate opposition.

Are they built in people’s backyards? There’s a famous case in Northern Virginia that has admitted they messed up zoning which gets cited in every story to make it look like they’re all built in people’s backyards, but the vast majority of them are in industrial zones.