Is he, though? It seems to me that a lot of his predictions were surprisingly close to the mark, especially given how long ago they were made.
If you scroll to the appendix he grades individual predictions.
One of Kurzweil's close-but-no-cigar failed predictions was "neural nets and genetic algorithms," killed off by the conjunction and being a couple years too early (2009 for increasing interest, and 2019 for wide use).
We've got things like 2009 - "Computers can recognize their owner's face from a picture or video. No." And ok, sure, but that has happened by 2026 and we have more than 2000 years of recorded history of people making predictions.
I don't think that situation reflects at all badly on Kurzweil except that he doesn't explicitly say he has a 15 year error bar. Which, yes, technically inaccurate, but it seems quite likely nobody would be talking about him if he spent that much time exploring the minor caveats.
And hitting him for the "and genetic algorithms" is verging on pedantry. Ok so genetic algorithms aren't a civilisation-level success that appears to be reshaping the fate of the species in the same way neural nets are. He was right that learning systems were going to be huge and he was off on a detail.
If he was often right-but-early about things that weren't even in the hypothesis space for everyone else, that would be huge, even though his dated predictions would technically be wrong. But this example seems way less exciting. Facial recognition was not a new or impossible-seeming idea, so the remarkable thing about his prediction was the part where he said "by 2009". (And yeah, 15 years is a short time compared to 2000 years, but 'recorded history of people making predictions' is not really a serious reference class for his predictions. He's a guy in the computer age making predictions about what computers will do.)
I'd say that 7% accuracy is on the low side and 86% on the high side. Looking through the list I'd put it more at 50-60% personally. For me that still means that I'd much rather hear about what he has to say about the potential future than most other people.
It's very easy to say 'person X made a highly specific testable prediction, while respectable people said nothing like it would ever happen, and it only 90% happened, so person X was a fool unlike all the respectable people', but it's a trap. In reality Kurzweil was directionally correct about most things, overspecified the details, and had optimistic timelines in the way that everyone has optimistic timelines about everything.
Can you give some examples of predictions he got roughly right where this applies?
(Not a gotcha, I'm genuinely interested, because this is the key for me when thinking about whether to give credit for 'close' or 'right but early' predictions. If you're predicting things that most others have dismissed as impossible, or nobody has even thought of, then it's pretty impressive and interesting when you turn out be even roughly correct. (I'll still ding your credibility if you are overconfident about dates and details, but I'll do that while paying plenty of attention to what you say next.) If you're predicting things that are already suspected to be possible, though, and what makes you stand out is your confidence and your timelines, then I'm not going to be very interested when some of your predictions turn out to be fairly close to the truth.)
2020-2050: Phone calls entail three-dimensional holographic images of both people.
This is totally possible. We could even do it on phones with fairly mundane consumer technology. We can do it with glasses, even. People just don't care. The prediction has yet to land but in spirit is correct.
Centuries hence: Computer intelligence becomes superior to human intelligence in all areas.
Anyone doubting that this will be true within centuries is nuts.
2009: People can talk to their computer to give commands.
At most a couple years early in technicality, and in spirit over a decade early.
2009: Computer displays built into eyeglasses for augmented reality are used.
True today, if not a particularly popular product, and later than suggested.
2009: A $1,000 computer can perform a trillion calculations per second.
Definitely true today. I think this was basically on time, too.
2019: Most people own more than one PC, though "computer" no longer means laptop or box-plus-monitor.
Freebie.
2019: Most learning is via adaptive courseware presented by computer-simulated teachers; human adults are counselors and mentors, not instructors.
We obviously could do this today, though it might not be a great idea for the students. Early, and socially blind, but basically right about possibility.
2019: Prototype personal flying vehicles using microflaps exist, primarily computer-controlled.
Basically wrong. There are eVTOL companies aiming for this, and people do have camera drones, but the sense it was meant wasn't predictive.
2019: Human-robot relationships begin as simulated personalities become more convincing.
Early, subscale, and fought against by providers, but this is a thing.
2029: Massively parallel neural nets constructed by reverse-engineering the human brain are in common use.
Ok people will mob me for saying this, but this was more right than wrong. Definitely at least a bit wrong.
> Later in Kurzweil's article, he says:
> > "So what does the future hold? By 2019, we will largely overcome the major diseases that kill 95 percent of us in the developed world, and we will be dramatically slowing and reversing the dozen or so processes that underlie aging."
> [...] I really do expect to put cancer, heart disease, the major infections, and the degenerative disorders in their place. But do I expect to do it by 20-flipping-19?
It's hard to be optimistic when it's been those 13 years plus another 7 and somehow measles is back again, although I admit that's one isn't a pure technology-problem.
[0] https://www.science.org/content/blog-post/ray-kurzweil-s-fut...
Looking back, he’s great at selling a future of possibility as long as you don’t track all the errors.
I encourage anyone interested in this to read On Bullshit by Harry Frankfurt, the best popular philosophy work in a long time.
Both Altman and Zitron are the opposite of Frankfurt’s bullshitter, because they both appear to evince genuine care for the truth value of their position.
(Frankfurt is very subtle about this, in that he distinguishes the kind of performative lying you’re suggesting as distinct in moral and rhetorical content from bullshitting. The liar wants you to believe a specific thing; the bullshitter wants to regale you.)
(Frankfurt’s characterization of the bullshitter rests on not just the truth value being absent, but also on the bullshitter’s misrepresentation of what he’s “up to.” I don’t feel that either Zitron or Altman is misrepresenting what they’re getting up to.)
Do you think misrepresentation has to be consciously deceptive? That it feels insincere to the person doing it?
(I have to admit a bias when it comes to Frankfurt: I don’t think On Bullshit is that convincing. In particular, I think Frankfurt doesn’t do a good job of motivating the connection between bull sessions and bullshit in his strong sense, and many of his examples - like the Pascal/Wittgenstein one - don’t demonstrate misrepresentation either.)
I can't really judge Zitron, but when it comes to Altman, I have absolutely no idea how you arrived at that assessment. In my view, he's clearly dishonest. I’ll remind you of his attempt to use government intervention to erect barriers to market entry for his competitors. Or his claims about AGI being just around the corner—claims that haven’t come true so far and were clearly aimed at investors. I’ve never heard a single statement from this man that struck me as honest.
The rest is noise, I don't care what minor predictions he was wrong about, he called the big trend back when nobody else could make a trendline.
The question is whether he sincerely believes his own predictions or if he cynically is aware that you can create a career for yourself being a guy who says bombastic clickbait-worthy things people emotionally want to be true, instead of measured assessments of reality.
Problem is, you wouldn't know Ed Zitron's name if every piece he wrote basically said "AI might be a bit overhyped short term but will have lasting economic impacts." Booooorrrring.
The reverse is also true. OpenAI and Anthropic aren't going to get much media attention if they don't make silly claims like "all white collar jobs gone in 2 years."
And no, this isn't a new problem due to "the algorithm." Media has always been like this. Zitron is just another Peter Schiff with younger skin. The problem is human nature in general.
Hence why AI isn't going to kill media. We don't actually want sober, rational assessments of all available information from hyper-intelligent LLMs. This is unsatisfying. We want emotional validation, drama, adversarial identity and spectacle. Truth is rarely what we are seeking.
"Correct" is not the word you're looking for here. More like "very effective". His strategy for manipulating human attention is very effective, but the correctness of his strategy isn't relevant here, so I'm not sure why you're bringing that up.
Autistically pretending the world is rational and not factoring this in is just as false as Zitron’s predictions.
Swapping those words changes nothing about that sentence.
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