The Peter Zeihan Podcast Series - Is the AI Revolution Here?

Episode Date: January 30, 2023

Today we answer the question that's been in the back of everyone's mind since The Terminator came out - is Skynet taking over? The short answer is no, but let me explain what is actually going on with AI...My Latest: https://mailchi.mp/zeihan/is-the-ai-revolution-here

Hey, everybody, Peter Zion here. We've had a lot of questions come in about AI and what that means for the workforce moving forward. What sort of activities should we expect to be replaced? What does this mean for economics and labor and politics? And are there any obvious winners either in terms of geography or sectors? What popular one that comes in is whether or not this is going to hit red states or blue states. more, for example. The cop-out answers, we don't really know yet because we're dealing with technologies that have yet to be invented, but there are a few general guidelines we have. First of all,

it's not so much that jobs get created or destroyed. It's that they change. And it's pretty common when you're dealing with an environment that has evolved because of technology. You know, jobs evolve too. We've been talking about technology overwhelming the workforce. Really the onset of the industrial revolution, and it obviously generates changes. We don't all live on subsistence farms anymore. The trick is whether or not the technology evolves faster than our political ability to adapt to the changing workforce conditions. And I would argue that at least at the moment, we're nowhere near that. I mean, yes, we're dealing with the information revolution. And yes, there is the possibility that's going to replace a lot of jobs, increase productivity

to the point that a lot of people just don't have anything to do. But we, that's all theory. Our experience in the last five years is, if anything, it's going to be the opposite. You see, the sort of things that IT evolutions do is it makes it's in the name, information, information tech. It manipulates information at a faster rate. But that is not where the uneducated people in our society are. Most of the uneducated people in our society are in lower class blue-color jobs. That is not something that AI can help with at all.

That's something that the advances we've seen in production. are almost irrelevant. AI instead is taking away those low to mid-skilled white-collar jobs, which is not normally what we think of when we think about the sort of jobs that can be destroyed. So we've actually, in the last three years, seems the greatest increase in take-home pay for low-skilled blue-collar workers, and over a century, and that has actually helped, in the case of the United States, narrow economic inequality to a degree that we have not seen since before the world wars. So if anything, the theory is proving itself wrong rather than right. However, if you're, say, a copy editor or a secretary, well, you might have some really big problems because AI already

has been able to deal with those jobs in a more efficient matter. You just don't need as many people. In fact, the blockchain, which is one of the things that undermines crypto, sorry, under Gerds crypto, not under mines crypto, is something that could be very transformative in things like healthcare. If you think about any doctor's office you've been in, there's that huge forest of staff in the back who are basically on the phone with the insurance agents every day, all day. Well, the whole idea of blockchain is that anyone who controls half of the pieces can grant others access. Well, in your health care records, that would be you. And if everything from that can be digitized than that entire flood of low-skilled white-collar workers in the back of every

doctor's office and hospital simply goes away. So it's probably not going to hit where we think it is, and it's probably not a red versus blue thing, and it's probably not a coastal versus interior thing. It's mid-levels of education versus the edges. If you're highly educated or low-educated, you look fine from this. Second, there's the issue of time. Now, obviously, these technologies continue but there's two reasons to expect that we're going to have a lot more time to make this adaptation that I think a lot of people give a credit for. Number one is as the baby boomers are retiring, which is happening right now, they are liquidating all of their investments and going into really boring stuff like T-bills and cash. That's not what funds IT startups. That's not even what funds

the big IT companies in Silicon Valley. For that, you need venture capital. You need a high velocity of money. Retirees are no good for that. And the whole, world is aging very rapidly and baby boomers are not a phenomenon limited to the United States. So we're going to see the amount of capital just kind of seize up in the entire space. At the same time, most of the world is running out of the 20 and the 30-somethings that are necessary to do the research and develop these technologies in the first place. So overall, we should expect the pace of technological evolution of the world to slow quite a bit in the two decades to come compared to the two decades we've just completed.

Second, we're not close to a general AI breakthrough. Let me explain what I mean by that. Artificial intelligence kind of falls into two general buckets. General AI is sky net. The idea that the machine can actually look at a situation, think, come up with a potential solution, and then act on it. Or nowhere close to that. I don't know anyone, even Elon Musk thinks we're going to be there before 2050.

And this is before you consider that the amount of capital and workers that are available to develop these sort of things is in the process of drying up. So probably we're looking at 2060, 2070 or beyond. We're not even close. The other type of AI is applied AI or mission-specific AI. And it's not so much artificial intelligence in the way that we kind of have it on our heads, but it is machine learning, but it's really more like machine programming. So you put in dozens, hundreds, thousands of if-then statements into a program

for it to execute. And as long as the conditions that are presented to the machine fall within the rubric of what you programmed, you're okay. But if you see something even a little out of context, the whole thing tends to fall apart. So an example. Let's say you're developing an AI driving program and you tell it what a stop sign looks like. What if the stop sign has a bumper sticker on it? Or graffiti? Or if it's on the side of a building as part of an ad. Applied AI can't recognize. those other conditions, and if you kind of widen your parameters to make a rounding error, then it's going to make very real mistakes in the very real world that any four-year-old couldn't. So if you need AI to do calculus, yes, they're light years ahead of what we as humans can do right now.

If you needed to make a decision based on a judgment call, they are still completely and utterly and competent. All right, but let's assume, let's assume that some of this happens anyway. and so we're going to have to deal with an AI system that is making decisions. What does that mean for the job industry? So historically speaking, this is not the first time we've dealt with this issue. In fact, for those of you remember, your 1800s political economic theory, good old Karl Marx, his old idea was that the future of the proletariat was to take over from the capitalists that once the industrial plant was built, then you could get rid of the,

the bourgeoisie and the proletary could live and do very, very well for itself because the machines and the industrial plant would be there to provide for everyone. Well, folks, he was wrong then, he's still wrong now. Universal basic income is the idea that we live in such a world of plenty that we don't need to work, but as we have seen the next last three or five years, if anything, the opposite is true. The productivity has... stalled in part because of tech, but moreover because we've discovered that as populations evolve in industrialization, we live longer, we have fewer kids, and that means after we urbanize five, six, seven, eight decades after, we're actually running out of young people to do a lot of the

lower skilled work. So if anything, Marx was completely wrong because the part of the population that he thought that would benefit the most from industrialization is at the current moment, actually not doing all that well, the middle class. It's the lower classes that are cleaning up right now. There are very, very few places in the United States at this point where if you were earning $15 an hour before COVID, you're still in that bracket today. You've been able to leverage the fact that there's a sharp labor shortage to move up. And that means you have a vested interest in the system. And it means if you decide to not work, there is no one who is willing to pay you to not work because there are jobs, jobs, jobs everywhere. So, in conclusion, is AI real? Yes. But we've been

thinking about it completely wrong. And most of the assessments that I have seen from almost everywhere are drawing the wrong conclusions when it comes to sociological outcomes. It's going to be important. It's going to change who we are. It's going to change how we live and how we work. But the word here is change. It's not a revolution. All right. That's it for me. I want to go get a snow shuttle. Take care.