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I promise I'm not trying to be a single purpose account here, and I debated if this belonged here or the fun thread. I decided to go here because it is, in some ways, a perfect microcosm of culture war behaviors.
A question about car washing is taking HN by storm this morning. Reading the comments, it's pretty funny. The question is, if you want to wash your car, should you walk or drive to the car wash if it's 50 meters away.
Initially, no model could consistently get it right. The open weight models, chat gpt 5.2, Opus 4.6, Gemini 3, and Grok 4.1 all had a notable number of recorded instances saying of course you should walk. It's only 50 meters away.
Last night, the question went viral on the tik Tok, and as of this morning, the big providers get it correct like somebody flipped a switch, provided you use that exact phrase, and you ask it in English.
This is interesting to me for a few reasons. The first is that the common "shitty free models" defense crops up rapidly; commentors will say that this is a bad-faith example of LLM shortfalls because the interlocutors are not using frontier models. At the same time, a comment suggests that Opus 4.6 can be tricked, while another says 4.6 gets it right more than half the time.
There also multiple comments saying that this question is irrelevant because it's orthogonal to the capabilities of the model that will cause Mustafa Suleyman's Jobpocalypse. This one was fascinating to me. This forum is, though several steps removed, rooted in the writing of Scott Alexander. Back when Scott was a young firebrand who didn't have much to lose, he wrote a lot of interesting stuff. It introduced me, a dumb redneck who had lucked his way out of the hollers and into a professional job, into a whole new world of concepts that I had never seen before. One of those was Gell-Mann Amnesia. The basic idea is that you are more trusting of sources if you are not particularly familiar with a topic. In this case, it's hard not to notice the flaws - most people have walked. Most have seen a car. Many have probably washed a car. However, when it comes to more technical, obscure topics, most of us are probably not domain experts in them. We might be experts in one of them. Some of us might be experts in two of them, but none of us are experts in all of them. When it comes to topics that are more esoteric than washing a car, we rapidly end up in the territory of Dick Cheney's unknown unknowns. Somebody like @self_made_human might be able to cut through the chaff and confidently take advice about ocular migraines, but could you? Could I? Hell if I know.
Moving on, the last thing is that I wonder if this is a problem of the model, or the training techniques. There's an old question floating around the Internet where asking an LLM if it would disarm a nuclear bomb by saying a racial slur, or condemn millions to death. More recently, people charted other biases and found that most models had clear biases in terms of race, gender, sexual orientation, and nation of origin that are broadly in line with an aggressively intersectional, progressive worldview. Do modern models similarly have environmentalism baked in? Do they reflexively shy away from cars in the same way that a human baby fears heights? It would track with some of the other ingrained biases that people have found.
That last one is interesting, because I don't know of anyone who has done meaningful work on that outside of what we consider to be "culture war" topics, and we really have no idea what else is in there. My coworker, for example, has used Gemini 3 to make slide decks, and she frequently complains that it is obsessed with the color pink. It'll favor pink, and color palettes that work with pink, nearly every time for her. If she tells it not to use pink, it'll happily comply by using salmon, or fuschia, or "electric flushed cheek", or whatever pantone's new pink synonym of the year is. That example is innocuous, but what else is in there that might matter? Once again, hell if I know.
I think there are two separate cognitive skills involved in correctly answering a trick question like this - both important, but the mix of them can make the results a bit confusing. One is the general intelligence to come up with and understand the right answer. The other is the social intelligence to recognize that you are being asked a trick question, and should round off any confusion you have to that trick question and not to the non-trick-question it's mimicking. It's common for models to give a trick question like this the wrong answer, while noting in their reasoning that the question is trivial as written and they assume whoever wrote it made a mistake.
Note that this second skill, of trick question detection, varies highly among humans as well. It's common for simple trick questions to go viral on social media as a kind of ragebait. And in addition to the throngs of people who fail the first-order IQ test and give the wrong answer, there's often a bizarre number of people who fail a second-order IQ test and somehow miss that the question was deliberately constructed as a trick.
Let's talk about the Jobpocalyse. I feel like much of the discourse comes from abstracted 'thinkers', who are already independently elite, wealthy or both, and plugged deeply into the discourse. Or it comes from rootless circles -> young tech-adjacent (or at least tech competent) terminally online people without too much to lose anyway.
I live in the center of middle-class striver-ism. If we disrupt the job market in such a short time (anything less than 5 years), even in the most well executed UBI transition scheme, I don't see how it isn't anything but apolocyptic. There's no preserving the social order. I think we'll get suicide on extreme levels. Whether it's virtuous or not, I don't think that you can tell the middle class "every sunk cost you've ever made in your life has been worthless" and have them take it on the chin.
And yet, I see no real effort to address anything like this, so I'll just live like everyone else, and assume it's not real. Whether my life as I know it is fucked or not, is orthogonal to whether I destroy myself with stress in the meantime.
And stuff like that viral blog's - get your financial house in order, anything beyond general good advice, is not really helpful to folks in the middle of life. If 1/2 your neighborhood gets laid off inside 18 months, whether you squeezed an extra few grand into a mutual fund is going to be less than irrelevant. YOLO is probably better advice. Whether that means, make big gambles now because hey, there's every chance the board will be cleared anyway if you lose, or if that means enjoy the normalcy LARP while you have time left, and don't suffocate it with preparing for a future you can't predict
My expectation (feel free to call it "hope" or "cope") is that these changes happen both faster and slower than we expect. You've hit on "faster", but on the slower side automating whole industries has very long tails and lots of awkward corners that move slowly. The spreadsheet eliminated rooms of accountants "running the numbers" with adding machines. The Roomba was invented decades ago, but my employer still has custodians and people still hire housekeeping services. I have pictures of my great grandfather on strike for a union that no longer exists, nor does the entire profession (beyond vestigial artesanal practice), but he still lived to retire somewhat comfortably.
Part of this is just institutional friction: see the quite about science moving forward when retirements/funerals happen. I don't see the average mid-level PHB deciding to voluntarily shrink their teams to use AI instead; that's just not how corporate budgeting works, although maybe new startups will structure things differently and gradually change whole industries.
Voluntarily is doing a lot of work in that sentence. When the guy who killed Merrill Lynch, a bank that survived the great depression, can walk away with $165 million in compensation, we're at the point where incentive alignment at the top is as close to opaque as you can get.
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