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Roughly 3 years ago, specifically in December 2023, I've reiterated my longstanding prediction that «the culture war's most important front will be about AI», and specifically AI accelerationism vs anti-AI/AI safety movement:
And the following political compass:
Seems like this was too much complexity for big tent politics in the US, at least so far; and the Trumpian State sees no use for the EA network, and instead (pretty rationally) perceives it as an uncontrollable alternative center of power. Instead we have, essentially, anti-AI left + pro-AI right (with some notable exceptions – eg. Steve Bannon, apparently, has been anti-China specifically because of his concern about Chinese AI progress, and now joins hands with Bernie Sanders). I've also failed to predict the salience and extent of Chinese open source dominance, as well as the bizarre datacenter water use backlash (charitably, can be shoehorned as Luddism?). Nevertheless, we've «succeeded» at the core task of making this a culture war front. The degree of (unnecessary) politicization of the issue is incredible. Trump is doing the yeoman's work, lumping it in with random Blue-coded ideas he disapproves of “Global “Warming,” where everyone was going to be dead by now, RUSSIA, RUSSIA, RUSSIA, UKRAINE, UKRAINE, UKRAINE, or Impeachment Hoax #1, or Impeachment Hoax #2.”. Jensen Huang enjoys his role as the kingmaker who has the King's ear. Sam Altman is opportunistic as usual but, after recent incidents, is genuinely spooked about AI risks (I have it on good authority that OpenAI really intends to slow down some internal projects specifically to bolster their oversight). The quasi-Masonic part is shaping up nicely, too – Dario Amodei, who's become the poster boy of Woke Left AI, promotes Embedded Evaluators with the central example being METR, very deeply connected to Anthropic and the broader EA scene. The EA itself is more explicitly Left-aligned now, despite efforts of some to paint them as TESCREAL eugenicists (the woke cancellation of Bostrom in Jan 2023 was the canary in the coal mine, Yudkowsky laments the missed opportunity of bipartisanship). There are clearly politically coded reports on prominent doomers.
This is all a bit meandering. What I want to know: how do you see this going further? We aren't anywhere close to the wall of capabilities; there are no walls in sight. Anthropic and OpenAI are holding back already, but their products will keep getting better, and fast. Google will make a comeback at some point (maybe in a couple weeks), xAI and Meta may catch up too. In my book, we (well, they) have practical superintelligence that's sufficient for both unprecedented productivity acceleration and really devastating, nation-crippling cyberattacks, which I guess will be discussed with Xi soon. At this rate, in a few months the level of capability Fable 5.1 or GPT 6 Astra will be mostly commodified and uploaded to HuggingFace (owned by Nvidia now). And those are relatively weak systems compared to internal models, which can build models that are vastly stronger still, without even any R&D breakthroughs, just by virtue of synthesizing stronger data trajectories and designing better RL environments. Superintelligence, in other words, is baked in. By Q1 2027 we'll see a jump from Astra that's at least as big as Sol => Astra. I fail to understand how that won't steamroll companies trying to build their moats on products downstream of frontier AI, labs need every bit of revenue to cover their costs, which will only increase due to growing self-imposed safety requirements; employers outside the AI sphere will also be increasingly feeling the heat. There's a whole ugly dimension of circular financing, too.
Americans as a whole are pretty pessimistic about AI even at these mediocre levels of diffusion (I am skeptical of this data that purports to demonstrate much lower adoption than in China, Americans are probably lying more due to widespread negativity on AI, but in any case AI isn't currently doing most of their jobs). Astra+ level models with very low error rate and 300 tok/s output totally can replace most knowledge workers. On the other hand, it seems that so far AI has not caused anything like mass unemployment, and perhaps economists have a point about comparative advantage, so that'll reduce the intensity of class dynamics.
Democrats are likely to sweep both chambers of Congress, which I guess is what Dario is hoping for and why he feels emboldened to antagonize Trump&Hegseth. Nevertheless, the needs of national security and GDP-maxxing (as well as the Executive's will) should prevent any nontrivial exogenous industry slowdown. So by default we'll see further crystallization of Red Accelerationism vs Blue Decelism, and as AI becomes more undeniably scary, that may begin to eat into the Red political base. It'll be interesting to watch, but I'm really uncertain as to how it'll go.
The mood is already turning against AI even while the labor market is strong, it’s hard to believe that won’t get much worse as large scale layoffs start to bite. As we know, corporations exist primarily to serve their employees rather than shareholders or customers, so (as @RandomRanger says below) this is more likely to be in the ‘the guy next door opens a factory with a tenth of the workers and half the prices’ form of creative destruction. That will force widespread changes in the labor market absent extreme political intervention1 , which necessitates politics, and could happen in a matter of months (or not). I also think it’s clear by now that a Chernobyl or at least Three Mile Island (although I expect the former) level casualty event is imminent, at least from my dilettante’s understanding of the HF attack, which will only make the backlash stronger.
The Chinese, of course, have much less of a social safety net than any Western country, a hypercompetitive entrepreneurial culture used to driving down margins, and a competition between provinces for subsidies that essentially encourages lossmaking businesses. All this means that even if CCP directives ban layoffs (and they will), that would not contain a labor crisis in most sectors. Inertia can only take you so far.
I don't think "large scale layoffs" is necessarily the only future here. I'll certainly admit it's possible, but historically automation hasn't always gone that way. A century ago, we had lots of accountants, and most of their time was spent manually balancing arithmetic, maybe with a mechanical adding machine. Along came the personal computer (earlier for large businesses with mainframes), and most of that work can be automated pretty trivially. Yet there are more accountants today than there were a century ago. What changed is that they're not doing arithmetic, and the complexity of what they do has grown substantially. For all the complaints about the growth of the tax code (and frequent related stunts by politicians), we are able to handle that complexity because we can offload the line-by-line balancing to software. Some of that complexity is probably wasteful, but some of it is also better auditing and accountability, or targeted governmental incentives — some, again, is probably wasteful, but some seems reasonable.
I don't have quite as coherent an argument (still a work in progress), but it's also the case that "recession caused by mass AI-driven unemployment" is actually a self-own by corporate AI overlords in limiting their upside. If you replaced half of human workers tomorrow at a cost savings, any not-truly-essential business is going to lose customers who can't afford their wares: tech companies fit pretty high on Maslow's pyramid, and most of the base ones are long-commodified — at one point, most of us were farmers, then along came the tractor. Nobody in the West is starving because they can't get a farmhand job. The cratering of farm employment is, in fact, why I get to work an office job, rather than out in the fields somewhere, and I'm not sure I'm worse-off for it.
But that latter part is, again, a half-formed argument.
Of the job categories listed in the 1960 US Census, supposedly only one has disappeared completely: elevator operator.
Nevertheless, I think the complexity argument might fail for accountants. Complexity actually favors AI. They are good at it.
When you talk to rich people, everyone is looking for an accountant. They all think that their accountant is bad and want a better one. I've only had bad ones personally. Now I just do things myself because I don't want to deal with errors. AI has been a godsend. I think it's likely that AI will do my taxes in April 2028.
But there is a silver lining for accountants: knowing which rules to bend or break. If it treats taxes like it treats code, AI will happily fill out a 500 page form so you can pay $0.04 to the state of Arkansas for some K1 you got from an oil services company. The accountant knows to throw it in the trash. They can tell you to ignore that letter from IRS because it doesn't get serious until the nth notice. They know how to ignore the rules that contradict the other rules. They know that certain tax dodges are okay because all their clients do them and never get audited.
I think it's somewhat similar to driving. The system only works because people know when to break the rules. Will AI break the rules? If so, will they be liable for that? Humans might stay in the loop just so they can break/bend the rules.
AI fails for accounting not because of complexity but because of care. Accountants have to get the numbers right, and occasionally hallucinating shit isn't going to cut it. Maybe it would work for mob accounting, but I suspect the mob wants their made-up shit to be less random.
The hallucination argument is losing power. Harnesses will fix hallucination much like they have for coding.
I'm not going to straight up ask Astra to do my taxes, but I'm fully confident that Astra+harness is capable. So now we just wait for the harness. No doubt lots of smart people are working on it.
Accountants don't get the numbers right anyway which is why I do my own taxes now. It's a boring, frustrating job and attracts people who like money more than having interesting work with predictable effects.
Harnesses fixing hallucinations is news to me. I just spent an hour today putting a Junior's head on straight after codex sent them down the garden path for a day and a half.
It's not really about "harnesses" as some dedicated tooling, it's about meta-instructions and models generally becoming good at following instructions over long horizons. Like, I just wrote in my AGENTS.md some stuff to the effect of "periodically spawn subagents for independent blind audits, create teams with different scopes and domain-customized personas, check with web access, sometimes step back, iterate until you get clean results", and even the latest DeepSeek will diligently execute all that and massively improve its reliability. Astra Ultra won't even need such handholding. They'll still make mistakes, rabbithole into irrelevant minutiae, perform suboptimally on cost, but for labs this is all easy to improve with More RL, and humans are flawed too. I am sure that a junior's level can be automated today.
And yet.
ChatGPT Sol absolutely.
insists on
writing.
Like this.
In a shitty.
broken up.
style.
If I ask it to demonstrate a writing concept or somesuch and there are people in the scene. It will happily tell what the problem is and how to supposedly prompt it away but will then keep on writing like that. So much for "good at following instructions".
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No, it most definitely is not.
Do you use these tools on a regular basis? My experience with hallucinations is that they are extremely reduced.
Same. I can't recall seeing one with Codex and 5.6-Sol.
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It is still a problem with whatever models people are using. Just had to deal with a pretty bad incident at work a couple of weeks ago (thankfully not one due to any failures on our part).
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