The continued development of artificial intelligence could have far-reaching social and economic implications. Matt Bruenig shares his thoughts on three issues where AI may radically change our behavior and self-understanding.
There is a lot of debate about whether artificial intelligence, large language models (LLMs) in particular, will make people smarter or dumber. The case for dumber is that LLMs can be used as a substitute for learning. Rather than struggling through a subject and working your brain around understanding it, you can just have an LLM produce the desired output. The case for smarter is that LLMs can be used like a very patient tutor who answers your questions and thereby helps you understand and learn things.
Generally speaking, I think the answer is obviously both. This is true even for a particular individual who may use AI to help them understand certain things better while also using it to help them avoid learning other things. This tracks my own experience. I have used AI to help me understand certain aspects of web programming better than before, while also using it to avoid learning R/ggplot2, which I now use extensively to produce graphs.
Across society, I think the answer varies, which could create some troubling educational disequalization. There are some people who, for internal reasons, just really like to understand and learn about things. These are the people who teach themselves things with audio, video, books, and other written materials, even outside of formal education. For people with that kind of curiosity and internal drive, AI-as-tutor will allow them to get smarter. But there are other people who don’t care at all to understand or learn things and have to be coaxed into it in various ways: parental/social/peer pressure, economic incentives, and so on. For those people, AI-as-replacement will probably result in them being dumber.
Collapse of Main Merit Indicator
For at least some part of human history, productivity had a big physical component. In such an environment, people who were more physically capable were presumably able to produce more and therefore had more “merit” in the way we currently define it. But industrialization converted a lot of physical labor into machine labor, reducing the relative economic value of being strong or fast or similar. Now intelligence reigns.
But what we can see from this little historical story is that what sorts of characteristics make someone have “merit” depends in large part on totally contingent technological environments. In one technological environment, physicality may be the primary indicator of merit. In another, intelligence may be the primary indicator of merit. In yet another, it is conceivable that neither individual physicality nor intelligence would matter that much for individual productivity and thus merit.
Our current society seems to have built an ideological edifice around the fact that certain mental traits fetch the highest labor incomes right now. We don’t just see that as a quirk of our current technological environment but instead read huge meaning into it. We believe that the economic inequalities that result from this contingent reality are even good, that they reflect that good people are getting paid well and bad people are getting paid badly, and so on. You can see this at the most extreme end in Silicon Valley, where it seems a lot of people who had certain mathematical and programming skills that happened to result in high pay starting about thirty years ago also imagine themselves to be world-historical geniuses.
I don’t know how far AI will actually go, but I find the idea that it could destroy our current model of merit quite thrilling. Already we have seen that AI can, for a few dollars, do coding tasks that used to fetch programmers tremendous sums of money. If this were to actually spread across a lot of highly paid, high-intelligence type tasks and jobs, that would be a pretty amusing state of affairs. What if these mental traits we put so much meaning into, in large part because of the labor incomes they attract, become as economically valuable as being able to quickly multiply four-digit numbers in your head? How long would it take for our current intelligence-based hierarchy of merit to fall apart?
I like the egalitarian possibilities of this. People believing that they are owed twenty times the income of someone else because they are smarter than them is pretty insane on its face but does seem to be compatible to some extent with social stability. If AI makes it so that this extra intelligence doesn’t really have much economic value, then these sorts of ideas become much less plausible.
Of course, we might replace intelligence with some other merit indicator and wind up in the exact same inegalitarian situation as before, with nobody ever stopping to ask themselves whether these temporary, technologically contingent hierarchies of merit are fundamentally silly and ridiculous. That would be a pretty bleak outcome but darkly funny as well. Maybe we just deep down love inequality and will find some other thing to base it on even if intelligence no longer works.
One Dark Possibility
If the AI maximalists are right, AI and much-improved robotics will make most human labor not really necessary. I have no idea if this is true. Right now, I don’t see anything like that, but the premise of this argument is that the technology is going to get a lot better than it currently is.
But what if (most) people really are hardwired by evolution or whatever to want/need to get up and go work for a boss and have this particular kind of structure and all that? That by itself is not so dark. In such a world, you could create all manner of essentially fake jobs for people who like jobs to go to. In that world, a job is basically like a hobby, and already some people have hobbies like this, where they play flight simulators or trucking simulators. So that’s fine.
What would not be fine is if most people had this preference for the job hobby while also preserving our current notion of deservingness such that they make everyone engage in the job hobby, even those who are totally fine doing other things with their time. So right as we finally win this great struggle against scarcity, we create a simulation of it because that scratches certain evolutionary itches we can’t shake.
Facts Only
* LLMs can substitute for learning by producing desired outputs instead of requiring struggle.
* LLMs can act as patient tutors to help users understand and learn.
* One individual observed using AI to improve web programming while avoiding learning R/ggplot2.
* The impact on society varies based on individual motivation.
* People with high internal curiosity can use AI-as-tutor to become smarter.
* People lacking motivation may use AI-as-replacement, potentially resulting in reduced learning.
* Merit historically correlated with physical capability, which was reduced by industrialization of labor.
* Current society assigns high economic value to specific mental traits.
* The author finds the idea that AI could undermine the current intelligence-based hierarchy of merit thrilling.
* AI can perform coding tasks for a small fee.
Executive Summary
Artificial intelligence, particularly large language models (LLMs), presents a dual effect on learning: they can serve as substitutes for rote learning or act as patient tutors to aid comprehension. The author observes that the impact on an individual is contingent, as seen in the example of using AI for some programming tasks while avoiding others. Societally, this creates potential educational disequalization depending on individual motivation. Those with high internal curiosity can leverage AI as a tutor to increase intelligence, while those lacking intrinsic drive may use AI as a replacement, potentially leading to reduced learning.
The discussion shifts to the concept of merit by examining how technological environments determine what constitutes "merit." Historically, physical capability correlated with productivity, but industrialization shifted value toward machine labor, and now intelligence seems dominant. The current societal structure assigns high economic value to specific mental traits, which is seen as contingent on the current technological setting. The author speculates that if AI automates high-value cognitive tasks, the economic utility of these mental traits might diminish. This outcome could lead to a collapse in the existing hierarchy of merit, though it is possible other metrics might replace intelligence as the primary indicator of worth.
The piece concludes by considering a dark possibility: if AI and robotics render most human labor unnecessary, and people remain wired for work structures, a simulated scarcity could be created through fake jobs that satisfy evolutionary preferences for work, creating an illusion of necessity even when physical needs are met.
Full Take
The core tension explored is the decoupling of intrinsic merit from external, technologically contingent economic valuation. The piece interrogates an ideological edifice built around the belief that specific mental traits equate to high income, arguing that this link is entirely dependent on the current technological environment. This creates a powerful vulnerability: if AI commodifies the skills underpinning these high incomes, the foundation of the meritocracy—the perceived reward for intelligence—erodes. The author suggests the fear of this collapse might be tempered by egalitarian possibilities, positing that devaluing extreme intelligence could foster greater social stability.
The consideration of "fake jobs" introduces a profound systemic concern regarding human agency and evolutionary drivers. If technological progress eliminates scarcity, the drive to work may persist as an evolved preference rather than an economic necessity. The fear is not just economic collapse but the creation of an artificial structure—a simulation of necessity—to satisfy deep-seated evolutionary demands for status and structure, regardless of actual productive output. This implies a risk where the struggle against scarcity is merely replaced by an equally compelling, yet fundamentally artificial, structure.
The narrative functions as a subtle critique of how we assign meaning (merit) to observable outcomes (income). It forces a re-examination of whether the structures we value—like cognitive superiority—are stable truths or temporary artifacts of the current technological regime. The final implication is that resisting this shift requires not just economic adjustments but a fundamental reassessment of what constitutes human worth outside of market-driven metrics.
Sentinel — Human
The text reads as a thoughtful personal reflection blending lived experience with abstract philosophical inquiry on the future of meritocracy under technological change.