\n
![](\"https:\/\/content.fortune.com\/wp-content\/uploads\/2024\/02\/GettyImages-1963529037-e1707768781911.jpg?w=2048\")
<\/p>\n [ad_1]
\n<\/p>\n
The robot jobpocalypse is already here, if you listen to media reports. Big Tech companies are beefing up their AI division while cutting jobs everywhere else; and AI has been directly blamed for at least 4,600 job cuts<\/a> last year, with experts predicting the ultimate fallout<\/a> could number in the millions of workers<\/a>. But Elon Musk will tell you that\u2019s not the real crisis: It\u2019s that people aren\u2019t having enough babies.<\/p>\n Last summer, Tesla<\/a> CEO Elon Musk said declining birth rates<\/a> were \u201cthe biggest danger civilization faces by far.\u201d In separate comments, Musk said at the time that he was \u201cdoing my best to help curb the underpopulation crisis,\u201d in response to a Business Insider report that he had secretly fathered twins<\/a> with a top executive at his brain-implant technology company Neuralink.<\/p>\n But it\u2019s very unlikely that AI will put everyone in the U.S. out of a job, argues MIT labor economist David Autor, and although he didn\u2019t touch on Musk specifically, he was describing the same undeniable reality. \u201cBarring a massive change in immigration policy, the U.S. and other rich countries will run out of workers before we run out of jobs,\u201d Autor writes in the paper, \u201cApplying AI to Rebuild Middle Class Jobs<\/a>,\u201d recently issued by the National Bureau of Economic Research.\u00a0<\/p>\n It\u2019s simple demographics, Autor writes. With birth rates<\/a> across the industrialized world and China<\/a> plummeting well below the roughly 2.1 children per woman needed to keep a population steady, large parts of the world are facing a severe worker shortage, he argues.\u00a0<\/p>\n \u201cThe industrialized world is awash in jobs, and it\u2019s going to stay that way,\u201d Autor writes. \u201cThis is not a prediction, it\u2019s a demographic fact. All the people who will turn 30 in the year 2053 have already been born and we cannot make more of them,\u201d he writes.<\/p>\n But simple employment isn\u2019t a guarantee of economic wellbeing, Autor notes (as anyone observing the downward mobility<\/a> of the American workers since the 1970s can attest.) That\u2019s where policy comes in. AI, Autor claims, has the potential to reverse the impact of the last 40 years of automation, in which computers have devalued manual labor and increasingly rewarded knowledge\u2014and he claims that AI can even grow middle-class, well-paid jobs.\u00a0<\/p>\n The key is to leverage AI\u2019s ability to increase human \u201cexpertise,\u201d he argues. Pre-AI, computers made information cheap and easily accessible, which boosted the value of expertise provided by highly paid professionals (e.g., doctors, lawyers, educators). They had \u201cfaultless and nearly costless execution of routine, procedural tasks\u201d along with an \u201cinability to master non-routine tasks requiring tacit knowledge,\u201d Autor writes. AI, while in its infancy, does precisely the opposite. Generative AI can riff on existing pictures without being specifically trained, and follow instructions without knowing all the rules. \u201cIf a traditional computer program is akin to a classical performer playing only the notes on the sheet music, AI is more like a jazz musician \u2014 riffing on existing melodies, taking improvisational solos and humming new tunes.\u201d<\/p>\n This capability means AI can be used to create better, fairer jobs\u2014by disrupting the very top of the elite workforce and giving everyone else a leg up, Autor argues.\u00a0<\/p>\n In Autor\u2019s telling, today\u2019s \u201cmodern elite experts such as doctors, architects, pilots, electricians and educators\u201d are the modern version of the artisans who were put out of work by the mass-mechanization during the Industrial Revolution. Like their 18th-century predecessors, today\u2019s experts spend years learning their craft in a type of apprenticeship, and then \u201ccombine procedural knowledge with expert judgment and, frequently, creativity, to tackle specific, high stakes and often uncertain cases.\u201d\u00a0\u00a0<\/p>\n The growing importance of \u201cexperts\u201d is one reason that the cost of education and health care have ballooned some 600% and 200% over the last 40 years, Autor says. And he\u2019s advocating for AI to take a chunk out of those elites\u2019 judgment and help lower the cost of living for everyone else.\u00a0<\/p>\n \u201cBy 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 educator,\u201d Autor writes. \u201c This would improve the quality of jobs for workers without college degrees, moderate earnings inequality, and \u2014 akin to what the Industrial Revolution did for consumer goods \u2014 lower the cost of key services such as healthcare, education and legal expertise.\u201d<\/p>\n To show how that could work, Autor used the example of nurse practitioners. The job of NP was basically invented in the 1960s to stave off a looming physician shortage; NPs receive additional training on top of a nursing degree to be allowed to run and interpret medical tests; diagnose patients, and issue prescriptions\u2014tasks that were once exclusive to doctors. Aided by the growth of technology, including electronic medical records and communications tools, this job has increased 40% in the last 20 years, with the median NP in 2022 earning $125,000<\/a>, or 50% more than the median household income.\u00a0<\/p>\n It\u2019s not likely that AI will make experts superfluous, Autor argues, since it is only a tool, like a chainsaw or calculator, and \u201ctools generally aren\u2019t substitutes for expertise but rather levers for its application,\u201d he writes. (Take a pneumatic nail gun, for instance\u2014it\u2019s indispensable for a professional roofer and a looming injury for an amateur.)<\/p>\n But AI can give a trained worker a leg up to do their best work while minimizing the drudgery, Autor says. \u201cAI used well can assist with restoring the middle-skill, middle-class heart of the U.S. labor market that has been hollowed out by automation and globalization,\u201d he writes.\u00a0<\/p>\n To be sure, the technology is still in its early stages, and governments will need to make policy to protect existing workers from unscrupulous applications of the technology (and perhaps even overeager cost-cutters in company leadership).<\/p>\n But as proof that it\u2019s not just a pipe dream, Autor offers three recent studies that compare workers with and without AI assistance. Programmers using GitHub Copilot, an AI coding assistant, are more than 50% faster than those without, according to one study<\/a>. Another NBER working paper found<\/a> that AI helped customer-service agents be more productive and attain experience faster (and helped them stay on the job much longer than previously.) And a study in Science<\/em><\/a> <\/em>that compared professional writers (marketers, grant writers, consultants and others) using ChatGPT found that AI helped writers at all levels. \u201cWhile the best writers remained at the top of the heap using either set of tools, ChatGPT enabled the most capable to write faster and the less capable to write both faster and better,\u201d Autor writes.\u00a0<\/p>\n Governments should embrace the AI-assisted future to allow more workers to regain \u201cstature, quality, and agency\u201d in their work, which has eroded over the past 40 years, he argues. If AI instead accelerates the race to the bottom, the results could be devastating, creating a world where everyone has a job but no one has agency.\u00a0\u00a0<\/p>\n \u201cA future in which human labor has no economic value is, in my view, an ungovernable nightmare,\u201d he writes.<\/p>\n<\/div>\n\nEmployed, but is it good?<\/strong><\/h2>\n
Consider the nurse practitioner<\/strong><\/h2>\n