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How accurate have Ed Zitron's AI skeptic predictions been?
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.
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
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:
And Microsoft's numbers have been (note that, for consistency, all numbers are calendar year numbers and not fiscal year numbers):
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 se