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For workers, bosses and everyone else, there’s something of a shared sense that we are entering a new economy, one shaped and determined by the power of artificial intelligence. What will work look like in twenty years? Will it be a sort of elevated, bespoke version of what we have now – or will “jobs,” in effect, be obsolete?
Plenty of prognosticators are suggesting that jobs will go away, that there will be, at least in the short term, massive unemployment. People I have seen speak at conferences this past year are calling for universal basic income to help deal with the changes AI will produce. Others are talking about the identity aspect of a job, and how that’s going to work. Some say that every human, in the AI age, will be a “manager” of his or her own smart tools.
But there’s another sort of lens to view this through, as well: starting with the idea that human labor, unlike other kinds of commodities, is not fully fungible.
“The telegraph and horse examples are clear cases of full substitution,” writes Seb Krier, a head engineer at Google Deep Mind, on Substack in January. “They also can’t necessarily adapt to do something else. The horse analogy fails because it treats labor purely as power output. It ignores the unique human capacity for complex, super-additive organization. You cannot stack a thousand horses to build a super-horse, but you can stack a thousand humans to build a corporation, a government, or a philosophy. Human utility is super-additive in a way that equine muscle is not.”
Here’s how Krier applies that to AI:
“’[AI being able to] do anything humans can do cheaply’ does not imply perfect substitution. It could, but it doesn’t necessarily - you need to do more work to demonstrate that. It’s important to distinguish between substitutability (the technical feasibility of replacing an input) and substitution (the actual economic outcome of input choices). Just because an input can be replaced doesn’t mean the optimal menu of production will result in that choice.”
That goes to the fundamental question, which is: if the market has a choice between using humans versus machines for a given set of tasks, how will it make those decisions?
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Here’s a newer Substack post from more recently where Alex Imas brings his own analysis. This one got picked up by my favorite podcast, where intrepid host Nathaniel Whittemore, as is his wont, read the whole thing verbatim. Imas begins by noting that after automating a bunch of processes, Starbucks reversed course, seeing that people still wanted a human touch to their lattes.
“Economics is the study of decision-making under constraints, i.e., scarcity,” he writes, setting the stage. “If advanced AI brings material abundance—if machines can produce many if not all forms of human production at very low marginal cost—does economics become irrelevant? No, we will still have scarcity, but the kind of scarcity that matters will change.”
Imas then enters into some analysis of classic Marxism, characterizing the adherents of the commodity viewpoint this way:
“If a machine can produce anything a human can, write the brief, generate the image, compose the song, determine the diagnosis from a radiology scan, then the human will be replaced across all facets of production and jobs will simply disappear. Labor will be replaced with capital.”
But he cites the work of David Autor and Neil Thompson in a paper that presents something different:
“They argue that AI won’t simply eliminate jobs; it will reshape the economic value of human expertise. Their framework distinguishes between expert and inexpert tasks within any given occupation. When automation removes the simpler tasks (as accounting software did for bookkeeping clerks), the remaining work becomes more specialized, wages rise, and fewer workers qualify.”
Now, after that, he notes that the same writers, in his words, “consider” something very like a collapse of work:
“A starker possibility: that AI advances to the point where human expertise loses its economic value altogether. Under this scenario, AI will eliminate labor scarcity and produce what Herbert Simon once called ``intolerable abundance.’’ Automation of production will no longer involve managing a workforce transition, for which we have prior episodes of automation to rely on. We will need tools to maintain social organization, income distribution, and democratic stability without the labor market that has historically held these together.”
That’s the kind of dire, chilling stuff that you expect from those who don’t think that human value will ultimately win out.
Imas’ own argument is different: he suggests that human labor might be able to thrive even in a scenario where AI can do lots of things well.
“The economics of structural change, combined with deep-seated features of human preferences, suggests that as people get richer, they don’t just want more commodities,” he writes. “They want things that aren’t commodities in the standard sense of the word.”
A skeptic might say that if people have to pay more for anything human, they’ll buy the cheaper thing. But maybe not. Imas talks about the “social aspects” of this, positing a “post-commodity economy” where the rise of relational value rewrites the rules. Here’s his clear prediction: “automated sectors shrink as a share of GDP; relational sectors grow.” Whittemore, in his following of this, talks about the ramifications of business moving from a supply curve to a demand curve, and what that means in this context.
In the rest of the lengthy post, Imas provides concrete examples of these kinds of economic happenings, ending with a reiterated thesis on how relational sectors will triumph:
“Education, care, hospitality, therapy, and various local services are, for reasons outlined elsewhere in this essay, categories where the value of the service is likely to be increasingly linked to the human providing them,” he writes, citing research by the BLS Consumer Expenditure Survey showing how households in the “top income quintile” chose more spending on relational purchases. “These sectors are not small parts of the economy---together, they employ nearly 50 million people in the US. This gives some credence to the claim that the relational sector will be a substantial overall share of the economy post-AGI.”
We’ll see.
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