AI 회의론자 에드 지트론의 예측은 얼마나 맞았을까

I was curious how well the predictions of the most widely cited AI skeptic I've seen (Ed Zitron) have done, so I looked at how his predictions panned out. To disclose my own biases, I've never had a particularly strong pro or anti AI progress position. For example, in 2022, I did a comprehensive look at predictions Futurists made, including well-respected folks like Kurzweil and found them to be generally wrong on both the prediction results as well as the reasoning. On the flip side, in 2015, I wrote about how people were underestimating AI's ability to displace humans in jobs and have repeatedly been on the record as saying that many people are underestimating AI's ability to displace humans from jobs. My position on AI has been extremely boring and is basically, "if something is currently happening, the people who are saying that it's impossible that it will ever happen are probably wrong". One comment I've seen from a lot of AI skeptics when someone responds to an AI skeptic is that all of the people who are saying that AI isn't fake are self-interested liars. Personally (to my obvious detriment), I have no particular financial interest in AI companies. I own whatever the standard share of them is via boring index funds. I have some seed stage investments, but just due to the timing and what's gotten big, that part of my portfolio is underweight on AI. I don't work at an AI lab or a company that supplies AI labs. I've mentioned being hilariously bad at interviews before, and I did interview at an AI lab a number of years ago and failed the phone screen in a performance that was the kind of performance that must've inspired Jeff Atwood's famous Why Can’t Programmers... Program? where he concludes that there must be a lot of fake programmers out there because nobody could fail a coding interview that badly if they knew how to program. I don't benefit in any particular way if AI does well, except insofar as anyone who holds broad index funds benefits, but I do care about accuracy. 2024: Meta, Google, and Microsoft are dying Because there are quite a few prediction results, let's look at one in detail before the complete list to get an idea of the kind of reasoning Zitron uses. We'll arbitrarily look at this November 2024 talk where Zitron says, among other things, the major tech companies (like Meta and Google) are dying and they're thrashing around on AI because they don't know how to grow . Zitron specifically named Meta as a company that's dying ("it's a dying product, and it's kind of a dying company"). Meta's revenue and profit (GAAP operating income) have been Period Revenue Profit Amount % Amount % 2023 $135B 16% $47B 62% 2024 $165B 22% $69B 48% 2025 $201B 22% $83B 20% First half 2026 $117B 30% $42B 10% When he talked about companies not knowing how to grow ("none of these companies anymore really know how to grow ... in the desperation to try to reignite growth in a dying ecosystem the tech industry is going to shove this [AI] shit into everything"), he named Google and then Microsoft. Alphabet (Google's parent company) has had the following revenue and profit numbers: Period Revenue Profit Amount % Amount % 2023 $307B 9% $84B 13% 2024 $350B 14% $112B 33% 2025 $403B 15% $129B 15% First half 2026 $230B 23% $80B 30% And Microsoft's numbers have been (note that, for consistency, all numbers are calendar year numbers and not fiscal year numbers): Period Revenue Profit Amount % Amount % 2023 $228B 12% $101B 21% 2024 $262B 15% $118B 17% 2025 $305B 17% $143B 21% First half 2026 $173B 18% $79B 19% Although this wouldn't be in the spirit of Zitron's statement, one could argue that Meta is actually dying, it just hasn't died yet. However, the reasoning in Zitron's argument is incorrect here—the Meta, Google, and Microsoft ecosystems are not dying. Given how fast these companies are growing (in terms of revenue and profit), it doesn't seem that AI is, as Zitron implied, some kind of desperation move they're reaching for because "they don't know how to grow" and are all out of ideas. I don't think it's worth spending this much text on each prediction, but the pattern Zitron used here is illustrative. To make the case that these things are dying, he pulls on minor issues that are not positioned to cause the very large changes he suggests are about to occur. For Meta, he cited some kind of alleged MAU drop for Facebook. Rather than use Meta's own MAU figures or any kind of revenue or profit numbers, he seems to have used numbers from Similarweb. My experience with 3rd party tracking numbers like this is that they're quite inaccurate and generally useless for anything other than a rough order of magnitude comparison, making the Zitron's cited decline meaningless (Meta's reported numbers show no such sustained decline). For Google, he cites Prabhakar Raghavan, who he calls truly evil and "a computer scientist class traitor that sided with the management consultancy sect", as having done some kind of grievous damage to Google search. In his rants about Raghavan, he never credibly establishes that Raghavan is doing severe harm to Google search, and the Google search engineers who've commented on his rant don't seem to agree with the Raghavan as sole or even major reason for search issues hypothesis . 1 But even if we posit that Zitron is right and the villain Prabhakar Raghavan defeated the hero Ben Gomes, causing some kind of issue for Google search, this still doesn't make the case that Google revenue growth is in trouble at large because they have a number of other major products (such as YouTube and Google Cloud) that could drive growth even if search wasn't growing. Every significant part of the chain of reasoning here is not only incorrect, it's not plausible if you know anything about Google or big companies in general. I'll be the first person to say that Google search quality has some serious problems and that Google has been increasing the relative priority of revenue over the user experience over time. This was a source of consternation for a number of user-focused engineers at Google when I was there in 2013. For one of the issues Zitron cites, ads being confusing to users, in 2013, I asked a search engineer about Google changing the background color of ads to look more like search results because there was a previous study that showed that more an ad looked like a search result, the more users got confused over whether a result was an ad or a real search result, and I'd heard that Google deliberately made the ads not look like search results to avoid user confusion. The search engineer said that because some people didn't want users to get confused, it was impossible to make ads nearly identical to search results in a single change because it would be too obvious what's going on. The way this was going to happen was that every time you A/B test tweaking ads to look a bit closer to search results, you make a lot more money, so the change would happen over multiple years in multiple parts, each small enough that the people who want to fight back against this kind of thing would have a hard time making a case. That happened just as this engineer predicted, but it was going to happen whether or not Raghavan ended up overseeing search. And, of course, that kind of thing happening doesn't cause Google to run out of room to grow and become desperate to reignite growth in a dying ecosystem. Whether or not you think Google should do it, it's something that makes Google more money. How do people cite Zitron? From what I can tell of how people cite Zitron, they cite him as an authority so they can say that this guy who looked at the numbers has made this claim, so their claim is backed up by the numbers. It turns out that if you look at the claims Zitron makes and know anything about the topic, the claims don't make sense, but I don't think that's the point. The point is one can say that someone looked at the numbers. The other point seems to be that this