And specifically, what does this imply for AI? There are two theories of equilibrium unemployment — search frictions, and efficiency wages — and they actually give diametrically opposite predictions for when search frictions in finding a new job fall. I conclude that frictions are the more likely explanation, but that LLMs may actually increase unemployment if our ability to apply exceeds the ability to sort.
This is a topic where macro and micro have a pretty big gap.
If you’re asking about measured large-group unemployment, you probably don’t get very good causality from any given change, and there’s no useful, simple model of the motivations and frictions of potential-employeers and potential-employees. It’s a very complicated matching market.
If you’re asking about some specific reasons that an individual may be out of work or become out of work, you’ll get a lot better result and some concrete reasons. But everyone you talk to will say “that doesn’t scale!”.
At its most useless modeling level, unemployment happens when some people don’t want to (or aren’t allowed to) accept the wage that someone can and will offer.
As far as A(G)I impact on job market is concerned—assuming a future where a word like job still matters—the main question is not just about ‘jobs’ but ‘jobs remunerated such as to sustain reasonable livelihood’, i.e. wages, and the latter depends less on the (indeed interesting though) friction/efficiency wage subtleties, but really on whether the scarcity value for our labor is completely crushed by AI or not. Chances are it will be indeed. The new scarcity will be resources, not classical human resources. Whether you search long and well, may be of second or third order importance.