AI is not the revolution that will be televised… yet.

Takeaway Points:
1. Jobs change, not necessarily get destroyed, due to technology.

2. AI is mostly taking away low to mid-skilled white-collar jobs and not affecting low-skilled blue-collar jobs.

3. The pace of technological evolution is expected to slow in the coming two decades due to the aging of baby boomers and the drying up of capital and workers.

4. There are two types of AI: General AI and Narrow AI. General AI is far from being achieved and not expected to be developed before 2060 or 2070.

Is it a revolution?

There have been a lot of questions about AI and what that means for us all moving forward. What sort of jobs should we expect to be replaced? What does this mean for economics and labour and politics? Are there any obvious winners either in terms of geography or sectors?

The cop-out answer is 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 can use to help divine.

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 since the onset of the industrial revolution and it obviously generates changes — we don’t all live on subsistence farms anymore. The trick is whether the technology evolves faster than our political ability to adapt to the changing workforce conditions. I would argue that at least for the moment we’re nowhere near that. I mean yes, we’re dealing with the information revolution and yes, there’s 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. That’s all theoretical. Our experience in the last 30 years is, if anything, going to be the total opposite. You see, the sort of things that IT evolutions do, well, it’s in the name: 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 are in lower blue collar jobs. That is not something that AI can help with at all. That’s something that the advances we’ve seen in productivity 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. We’ve actually in the last three decades, seen the greatest increase in take home pay for low skilled blue collar workers in over a century. And that has actually helped 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 secretary, well, you might have some really big problems because AI already has been able to deal with those jobs in a more efficient manner. You just don’t need as many people. So it’s probably not going to hit where we think it is. But I do think it’s a mid level 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 moving, 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 us 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 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. Retires are no good for that. The whole world is aging very rapidly, and baby boomers are not a phenomenon limited to the United States or Australia.

So we’re going to see the amount of capital just kind of dry 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 — ChatGPT is cute, but it doesn’t know what its writing. Let me explain what I mean by that. Artificial intelligence kind of falls into two general buckets: General AI and Narrow AI.

A tale of two AI’s

General AI is, you know, SkyNet. The idea that the machine can actually look at a situation, can come up with a potential solution and act on it. We’re nowhere even close to that. I don’t know anyone, even Elon Musk, who thinks were 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 just not even close.

The other type of AI is Narrow AI or mission specific AI.

It’s not so much artificial intelligence in the way that we kind of have it on our heads, but it is machine learning. So you train these things, put in dozens, hundreds, even millions of if-then statements and as long as the conditions that are presented to the machine fall within the rubric of what it’s been trained, 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 it ad. Narrow AI can’t recognise those other conditions and if you kind of widen your parameters to make it 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 or paint a picture, yes, 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 incompetent.

Moving on…

Ok, so 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 who remember your 1800s political, economic theory and good old Karl Marx — his whole idea was that the future of the proletariat was to take over from the capitalist. That once the industrial plant was built, then you could get rid of the bourgeoisie and the proletariat could live and do very, very well for itself because the machines and the industrial plant would be there to provide for everyone. Well K Mart shoppers, he was wrong then and 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 in the last three or five years, if anything, the opposite is true. That productivity has stalled in part because of tech, but moreover because we’ve discovered that as populations evolve in industrialisation, we live longer, we have fewer kids and that means after we urbanise 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 industrialisation 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, Australia etc 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 labour shortage. That means you have a vested interest in the system, 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.