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Reading David Autor’s recent essay in NOEMA got me thinking deeply about the future of work in the age of artificial intelligence. While many are understandably anxious about the impact of AI on jobs, Autor makes a compelling case that “AI will change the labor market, but not in the way Musk and Hinton believe. Instead, it will reshape the value and nature of human expertise.” This framing resonated with me and I believe it deserves further exploration.

Autor’s starting point is that despite the fears of tech luminaries like Elon Musk about AI leading to mass unemployment, the demographic reality is that most rich countries are actually facing the opposite problem. As he notes, “Due to plummeting birth rates and a cratering labor force, a comparable labor shortage is unfolding across the industrialized world (including in China).” In other words, we are more likely to run out of workers before we run out of jobs. This means that the key question is not whether there will be enough work, but rather what kind of work will be most valuable.

This brings us to Autor’s central insight about expertise. As he explains, “Expertise is the primary source of labor’s value in the U.S. and other industrialized countries. Jobs that require little training or certification, such as restaurant servers, janitors, manual laborers and (even) childcare workers, are typically found at the bottom of the wage ladder.” Expertise commands a premium in the market when it is both necessary for a task and in scarce supply.

The challenge is that the computer era undermined and devalued many forms of “mass expertise” in routine, rule-based work while concentrating rewards among a small set of highly educated professionals. “By making information and calculation cheap and abundant, computerization catalyzed an unprecedented concentration of decision-making power, and accompanying resources, among elite experts.”

But here is where the story gets interesting. Autor argues that AI could invert this dynamic by enabling a much wider set of workers to take on elements of higher-stakes decision making that are currently monopolized by elite professionals. The reason, he explains, is that “artificial intelligence can weave information and rules with acquired experience to support decision-making, [so] it can enable a larger set of workers equipped with necessary foundational training to perform higher-stakes decision-making tasks currently arrogated to elite experts, such as doctors, lawyers, software engineers and college professors.”

I find this to be a powerful and hopeful argument. If AI can be responsibly deployed to augment the capabilities of workers with more basic certifications and training, it could help rebuild the hollowed out middle of the labor market. As Autor puts it, “AI is a tool, like a calculator or a chainsaw, and tools generally aren’t substitutes for expertise but rather levers for its application.”

Imagine, for example, if well-trained nurses could use AI guidance to diagnose and treat routine medical conditions, or if paralegals could leverage AI to draft standard legal documents. “By providing decision support in the form of real-time guidance and guardrails, AI could enable a larger set of workers possessing complementary knowledge to perform some of the higher-stakes decision-making tasks currently arrogated to elite experts like doctors, lawyers, coders and educators. This would improve the quality of jobs for workers without college degrees, moderate earnings inequality, and — akin to what the Industrial Revolution did for consumer goods — lower the cost of key services such as healthcare, education and legal expertise.”

Of course, this is not a given and we will have to be proactive in steering AI in this direction. We need robust training and support structures to ensure that workers can effectively and safely use these AI tools. We need strong governance frameworks and accountability measures to protect against misuse and bias. And we need to grapple with complex questions about liability, credentialing and the evolving roles of traditional professions.

But these are challenges worth taking on. The alternative is to allow AI to continue to concentrate knowledge work in an ever-smaller sliver of elite experts while consigning the majority to low-wage, low-skill jobs. By empowering more workers to leverage their own expertise in new ways, AI could be the key to building a future of work that is not only more productive, but more balanced and equitable. As Autor puts it, “AI offers vast tools for augmenting workers and enhancing work. We must master those tools and make them work for us.”

I couldn’t agree more. The age of AI will be defined not by the technology itself, but by the choices we make in how to harness it. Let us choose to make it an age of shared prosperity and human potential.

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