The New Jobs AI Will Create

**Nathaniel Whittemore** (0:00)
Today on the AI Daily Brief, the new jobs AI will create. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
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One of the big points of discussion for this week has been the idea that there is this ever so subtle shift in the AI jobs narrative. It would be going way too far to say that this was becoming anywhere near mainstream, but you're starting to see more people at least question the premise that AI and agents getting better means people will have less work. And yet even among those who are arguing that the AI job apocalypse narrative is way overblown, the argument tends to be much more backwards looking. It's looking at the way that productivity has previously impacted industries and extrapolating that out to the future. That's well and good, and all of that is important. But I think it is a significant failure of the AI industry to take the next step and actually start to explore the type of jobs that there will be in an AI-enabled future. The sheer tonnage of time spent on assessing which jobs are most at risk compared to the almost zero time exploring what types of new jobs will be created represents one of our great failures and leaves people who want to be optimistic about the future clinging to vague hand-wavy notions about what those jobs might be. Now from the standpoint of sheer epistemic humility, of course, we have to be careful about arguing with any sort of confidence what specific things will be created in the future. In other words, the more specific our future predictions, the less likely to be right they are. But that doesn't mean that we can't at least explore from first principles how we think the change is going to play out if indeed it is not going to be the mass destruction of white-collar work that some are promising.
So what I'm going to attempt today is talk about, one, the fundamental problem and the hidden assumption in most of the job apocalypse narratives, two, what opens up when you correct that assumption, three, how to deal with the AGI objection, and four, a real walk through a specific sector and some jobs that I could see very plausibly being a part of the future and representing meaningful amounts of employment. So let's talk first about that hidden assumption. AI is mostly analyzed right now as a labor supply story. In other words, AI increases the supply of labor, so labor gets cheaper and workers get displaced. But all of this rests upon the presumption that demand stays constant. This is another way of framing the lump of labor fallacy. The idea that there is a set amount of work to do, so if technology comes and does some of that work, that means that humans aren't doing that work, which means that those humans don't have any work to do. What it doesn't take into account is the expansionary nature of economies and the ability of demand to expand to absorb more supply.
Now I don't want to spend a lot of time on the historical arguments here. As I mentioned, that's the main substance of pretty much all other arguments along these lines. Yet it is worth noting, of course, that the assumption that demand stays constant as the supply of labor increases has never held true, and so if we are just going from historical precedent, it is unlikely to be true this time either.
The more important question, if we are trying to actually interact with people's lives as they are lived now, not just provide a history lesson, is to ask where demand will expand. Basically, what parts of the economy could actually grow as AI allows us to produce more? And I think what is important to note is that demand elasticity actually comes in a variety of different forms. The one that is most obvious is of course pricey elasticity, i.e. I wanted the thing but it cost too much. If AI makes a thing cheaper, new buyers can enter the market. A second category of demand elasticity is access elasticity. I wanted it but I couldn't get it. Now whereas AI supported price elasticity because it lowered the cost floor, in this case we are talking about AI reducing provider scarcity, or wait times, or geographic barriers, or other types of institutional bottlenecks. Basically, instead of it just being cheaper, AI makes a good or service more readily available.