AI Bubble: ‘This is dumber than WeWork’ | Ed Zitron

We're reaching this thing where we're realizing that everybody made a huge mistake. Everyone has invested in this thing for really effectively no reason. The actual data keeps showing that there is no productivity growth. What we're seeing here is the beginning of a hysterical episode following another hysterical episode where everyone said that something was happening when it wasn't. And I sound sarcastic, but look at the data. 90% of them said no impact on employment or productivity. Literally nothing changed other than they spent a lot of money on something and uh everyone had to use it. But yes, this is WeWork too except it's so much worse.

Thanks for having me. I saw a study by the National Bureau of Economic Research which revealed that 6,000 CEOs that it surveyed across the US, Europe, and I think Australia as well. 90% of them saw no impact on employment or productivity in the last three years from the adoption of AI. The study points to the information revolution of the computer where computers were sold and productivity growth was expected. But in fact, due to the overwhelming amount of information that these computers are producing, productivity actually slowed. I mean, anyone that is familiar and uses AI is probably hearing alarm bells at this point because they know that that's kind of what's happening now. There's just too much information being made by AI that it's actually slowing things down. Do you think history is repeating itself?

I mean, 1948, we'd also lost a lot of people very recently due to a war, and on top of that, the introduction of the computer was nothing like the introduction of AI. Mini computers sound small, they were very large. These were roomsize computers and then eventually terminalsize computers, what you would now find as a server act. It was one computer, it was the very early days of what they could actually do. In this case, when it comes to AI, it's one of the most evenly distributed and accessible things of all time. You actually can't get away from it. It's harder to not use AI than it is to use it because if you load a product, go use Google, you type in a search, neural language model, you have to use that now. You pick up your phone. Oh, Apple Intelligence wants to read you your text messages. You didn't ask, but it's there. You load every single app and it's got some weird pop-up. You go into Instagram. Meta AI wants to harass you and generate an image. If AI was gonna help, it would have been helping already. And I think we're entering this point where this is nothing. We're at the beginning of history. We're not at the end of history, Mr. Fukuyama, which I realize is a misquote, but we're not at a point where, oh, this is just the beginning. We're reaching this thing where we're realizing that everybody made a huge mistake. Everyone has invested in this thing for really effectively no reason. The actual data keeps showing that there is no productivity growth. There was another study uh the other day where it was like 75% of chief information officers were finding that they would have to in the next 6 months prove that AI hadn't worth or they'd have their budgets cut. I realize we've seen over a trillion dollars invested since 2022. Now, if you count the venture capital and all the capex, we've seen all of this money. We've had AI screaming in our ears. Every time we open a drawer, there's an AI in there. And this large language model in everything now. And nothing seems to have happened other than the birth of a new, more annoying Twitter personality. I think what we're seeing here is the beginning of a hysterical episode following another hysterical episode where everyone said that something was happening when it wasn't. And I sound sarcastic, but look at the data. 90% of them said no impact on employment or productivity. Literally nothing changed other than they spent a lot of money on something and everyone had to use it. Accenture is now saying that they are forcing people to use the AI. There will be checking and there will be your performance evaluation will be based on your use of AI. It's what happens when something isn't really working.

Great example, when the iPhone came out for example, we were still in the early days of bring your own device with software companies or companies. So you wouldn't be able to just bring any phone with you. You would have to have one provided by the company. There was a growth of companies that did BYOD. But you had this thing called shadow IT happening. You had people secretly using their iPhones. And indeed, shadow IT spread into other kinds of software. People were using the software they wanted to use at work. It was the opposite of being forced. In fact, they were using it without their IT managers liking it. This is the opposite. This is the boss saying, 'No, use my software. Use it. Use it, you pig. I want to see you using AI because we're in the era of the business idiot. The people that run these companies don't do real work. They're pushing AI because everyone's blaring in their ear that AI is important. When it comes to actually doing real work, it just doesn't seem to do it. Even the supposed speed ups for software engineers, what does that actually result in? What is the result of this? What is the thing that's actually happened? No one seems to be able to tell, which is crazy considering the amount of money invested.

I mean, it already is, but not through choice. It already is very common. They're shoving it down our throats. It's as common as a laptop because when you load a Windows 11 laptop, now co-pilot's there. It's like a vagrant moved into your basement. It's like a person's crawled through your vents and starts telling you that it could generate a summary of your emails. It's commonplace, but not through any consent from the user side. I don't think these models are improving in a way that makes them really essential at all. And I think that the thing is you can never fundamentally trust them. The ultimate technology behind large language models makes them inherently untrustworthy. Your use and trust of large language models ultimately comes down to how much you care about the information you have being correct or how much trust you have in your ability to verify it. Now, if one of the few use cases that people can actually quote of large language models is research, how in the world can you trust research from something that hallucinates? Oh, they're getting rid of hallucinations. No, they are not. OpenAI put out a study last year that said that hallucinations are an inherent part of large language models. So they can't beat them. So I guess you just eventually trust them. I had someone the other day say, 'Oh, we got something right about macrobiology.' Did it? Can you say for sure? If the only way for you to confirm whether something is correct is that you knew it already, then why the bloody hell did you get research in the first place? Confirmation bias. I don't know. So, it's really what are they improving? How are they improving? What is the end point? That's the ultimate thing of this conversation. It's where's the beef? What what is it that I meant to be looking at and excited about? And where is the point when this is good enough? Because right now it isn't. And that's before you get to the fact that all of this is subsidized.

Yes. I think that yeah, sure there's you have if you hear about AI and everything, you're going to go, I should probably check this out cuz no one will stop talking about it. But Google did a crazy one. Google Gemini, hundreds of millions of users suddenly. How'd that happen? Oh, right. They changed Google Assistant on every Google device to be Google Gemini. Traders hate this one trick. Uh Microsoft doing the same thing with Microsoft 365 co-pilot rename a thing. Suddenly you got all these users. Yay. I'm sure that Google also considers every user of Google Docs who has a Gemini popup or Microsoft considers every single user that has a co-pilot popup on Word or Google Docs to be an active user of Gemini or co-pilot. This is just rigging the dice. And this is not something you have to do if something is useful. It's something you do if you're just trying to deceive people, which is what they are trying to do. If these things had to stand on their own two legs, no one would really care.