{"id":387402,"date":"2026-04-19T15:21:11","date_gmt":"2026-04-19T15:21:11","guid":{"rendered":"https:\/\/www.newsbeep.com\/nz\/387402\/"},"modified":"2026-04-19T15:21:11","modified_gmt":"2026-04-19T15:21:11","slug":"the-economist-who-was-terrified-of-ai-just-found-a-rare-reason-for-hope","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/nz\/387402\/","title":{"rendered":"The economist who was terrified of AI just found a rare reason for hope"},"content":{"rendered":"

Alex Imas didn\u2019t arrive at optimism easily. The University of Chicago economist<\/a> economist occupies an unusual space in being one of the leading researchers on AI\u2019s labor market impact, but also one of its most avid adopters. Unlike many of his peers, he is taking the doomsday scenarios, perhaps best exemplified by Citrini Research\u2019s<\/a> viral essay on \u201cghost GDP<\/a>\u201d and spiraling deflation, very seriously.<\/p>\n

If automation eliminates most jobs and the wage share collapses, the people with money\u2014capital owners\u2014will be already satiated, while displaced workers can\u2019t afford to buy anything. Demand collapses. The economy shrinks. While Imas has written that he finds actual negative economic growth unlikely<\/a>, he said the scenario of high unemployment and a drag on the economy as a result of that unemployment is worth taking seriously.<\/p>\n

\u201cMy first reaction was to be very scared,\u201d Imas told Fortune. \u201cI needed to work things out carefully in order to be less scared\u2014not to convince myself not to be scared, just to look at history and look at people\u2019s preferences, bring these things together.\u201d<\/p>\n

Wall Street takes Imas\u2019 warnings seriously, too. A Morgan Stanley<\/a> research note last month recommended that investors follow Imas as a primary resource on AI\u2019s employment impact, saying he was among the valuable third-party resources on the topic. <\/p>\n

Imas is no armchair theorist: his research has appeared in the\u00a0American Economic Review<\/a>, the\u00a0Quarterly Journal of Economics, and the\u00a0Proceedings of the National Academy of Sciences<\/a>, and he co-authored a recent update of the behavioral economics classic The Winner\u2019s Curse<\/a>, with Nobel laureate Richard Thaler<\/a>. He may be getting most notoriety for his widely read Substack,\u00a0Ghosts of Electricity<\/a>. He wasn\u2019t aware of his appearance on Wall Street research desks, when told of Morgan Stanley\u2019s citation, \u201cthat\u2019s funny \u2026 I didn\u2019t see that.\u201d<\/p>\n

The reach of\u00a0Ghosts of Electricity\u00a0has surprised him more broadly. Imas started the newsletter with a specific ambition: to write with the rigor of an academic paper but for an audience far wider than journal editors, reaching economists, AI researchers, technologists, and policymakers at once. He said it has worked beyond what he anticipated, with responses coming in from, for instance, his mother-in-law\u2019s friends. He recently sat down with a neighbor, installed Claude on her computer, and watched her start building apps from scratch within an afternoon. \u201cThe ideas need to be out there broadly for a very broad audience,\u201d he said.<\/p>\n

And after several months of writing and rewriting, Imas has something for the doomsday crowd to digest: a vision of how the AI economy could work out not so badly. It\u2019s similar to an argument that has been increasingly appearing in the pages of Fortune. He opens with the example of Starbucks<\/a>.<\/p>\n

The Starbucks signal<\/p>\n

Starbucks is a $112 billion company selling one of the most standardized products in the modern economy. The technology to remove human labor from its stores has existed for years. And yet, after years of cutting staff and installing automated processes to protect thin margins, CEO Brian Niccol recently reversed course entirely. Handwritten notes on cups, ceramic mugs, comfortable seating\u2014human details\u2014had proven more valuable to customers than efficiency. More baristas are being hired. Automation is being rolled back. (Starbucks is on ChatGPT<\/a> as a beta in a way that ideally leads to drink discovery<\/a>, but that is distinct from its in-store strategy.)<\/p>\n

For Imas, Starbucks\u2019 shift is telling. As AI makes commodity production cheaper and more abundant, he argued in a recent Substack, \u201cWhat will be scarce?<\/a>\u201d certain things just can\u2019t be commodified in the coming AI world. These are things that Starbucks\u2019 Niccol seems to know: human presence, social connection, provenance. They will become more scarce, he argued, and therefore more economically valuable. The question he spent months of writing and revising on is: why, exactly, and how far does that logic extend?<\/p>\n

For its part, Starbucks referred Fortune to previous company communication on the subject of AI. The company says its approach to AI<\/a> is \u201cpractical and grounded.\u201d The company said it wants to \u201cuse AI where it helps partners deliver exceptional craft, deepen customer\u00a0connection\u00a0and improve the rhythm of the coffeehouse. If it does that, we scale it. If not, we move on.\u201d <\/p>\n

\"\" <\/p>\n

From farms to the \u2018relational sector\u2019<\/p>\n

The intellectual scaffolding is structural change theory<\/a>\u2014the economics of what happens when technology makes one sector dramatically more productive. The famous example, also beloved of Fundstrat\u2019s Tom Lee<\/a>, is that around 1900, 40% of the American workforce farmed. Today, it\u2019s under 2%. People didn\u2019t stop eating; they just stopped spending most of their time making food once it became commoditized and cheap. The economy didn\u2019t collapse\u2014it transformed, reallocating labor toward manufacturing and then services as incomes rose. Imas argues the same dynamic will play out with AI: \u201cThe economics of scarcity won\u2019t disappear, it\u2019ll just relocate.\u201d <\/p>\n

Drawing on a landmark 2021\u00a0Econometrica\u00a0paper<\/a> by Diego Comin<\/a>, Danial Lashkari<\/a>, and Mart\u00ed Mestieri<\/a>, he noted that income effects\u2014not just price effects\u2014account for over 75% of historical patterns of sectoral reallocation. In other words, when people get richer, they don\u2019t just buy more of the same things, which are now cheaper. They want\u00a0different\u00a0things, namely goods and services with high \u201cincome elasticity,\u201d meaning demand for them grows faster than income itself.<\/p>\n

The behavioral ingredient Imas adds is rooted in the French philosopher Ren\u00e9 Girard<\/a>\u2018s concept of\u00a0mimetic desire<\/a>: we don\u2019t want things purely for their functional value, but because others want them\u2014and because others\u00a0can\u2019t have\u00a0them. In experimental research with colleague Kristof Madarasz<\/a>, Imas found that willingness to pay for an identical good roughly doubled when subjects learned a random subset of people would be excluded from purchasing it. In follow-up work with Graelin Mandel<\/a>, AI involvement in creating a product dramatically reduced that premium because people perceived AI-made goods as inherently reproducible, undermining the scarcity that drives desire.<\/p>\n

The implication is that as AI commoditizes more of the economy, spending and employment will migrate toward what Imas calls the \u201crelational sector,\u201d which brings his Starbucks analogy back around. People will pay for things that have a distinct human element to them. In other words, middle-class consumption patterns tomorrow will look like wealthy ones today.<\/p>\n

Imas told Fortune there is already copious empirical support for this idea hiding in plain sight: today\u2019s billionaires, with no financial constraints whatsoever, spend enormous amounts of time on podcasts, at live performances, and on social platforms, consuming and producing human interaction. <\/p>\n

\u201cYou could be alone on an island consuming all the movies, all the video games, all of technology, everything you want,\u201d Imas said. \u201cBut most of the time, these billionaires, they\u2019re on podcasts. They\u2019re out there on Twitter<\/a>, interacting with people, they\u2019re going to performances, they\u2019re consuming relational goods, basically, or trying to provide relational goods, like the need for socialization to be around humans.\u201d<\/p>\n

The demand for human connection, he argued, has no natural ceiling because it is fundamentally comparative, never fully satiated. <\/p>\n

Not artists \u2014 nurses, teachers, baristas<\/p>\n

Imas is careful to distinguish his argument from a romantic vision of a world full of painters and performers. \u201cA lot of people\u2019s reaction [to the essay] was focusing on performers and art. I think those are kind of red herrings,\u201d he said. \u201cStarbucks workers are not performers. They\u2019re not artists. They\u2019re just people. They\u2019re human beings and people value interacting with human beings\u2014not from a highbrow or artistic or entertainment perspective, but just from a basic desire for socialization perspective.\u201d<\/p>\n

The relational sector, in his framework, encompasses nurses, doctors, teachers, therapists, childcare workers, personal chefs, and hospitality workers. These sectors together already employ nearly 50 million people in the United States. Many existing jobs won\u2019t disappear wholesale but will transform: as AI automates the routine tasks within a teacher\u2019s or doctor\u2019s workday, what remains\u2014the emotional support, the attentiveness, the relationship\u2014becomes the core of the job and the core of its economic value. Fortune recently made similar arguments<\/a>, noting that those jobs with a human factor or relational aspect are already pulling in above-average salaries, particularly in nursing and teaching: Nurse Dana from The Pitt<\/a> is a salutary example.<\/p>\n

Right now, Imas explained, doctor and teachers are doing jobs that are half relational and half vulnerable to automation, and some of those surely will be. Imas said \u201cthe thing that\u2019s not being recognized right now\u201d is how those jobs will evolve to be more relational as AI advances. \u201cThe widget maker may be gone. The truck driver may be gone, because tasks in that job don\u2019t have a relational component. But there\u2019s a lot of jobs right now that have a relational component, which will become relational jobs.\u201d<\/p>\n

\"\" <\/p>\n

The sports car with no roads<\/p>\n

That theory gets a real-world stress test inside a large medical nonprofit, where a senior data scientist\u2014who asked not to be identified by name or employer\u2014told Fortune that he has spent the past six months watching his organization\u2019s newly formed data strategy committee deploy an enterprise ChatGPT account to the entire staff. After weeks of all-hands presentations, the only use cases that management could articulate were: writing emails and summarizing emails. In fact, \u201cthey wanted employees to be AI champions to come up with other use cases, but few have been interested.\u201d<\/p>\n

The data scientist said that his actual work\u2014running statistical analyses on cancer patient data for one of the country\u2019s largest medical databases\u2014involves protected health information that the tools aren\u2019t even authorized to access.<\/p>\n

This doesn\u2019t mean that AI wasn\u2019t capable of essentially doing his job. In fact, he said that after the first release of ChatGPT years ago, he built a cancer survival-risk calculator with that tool in under a month. Because of the relational aspect, though, it\u2019s been sitting in legal review indefinitely. He agreed with Fortune\u2019s metaphor<\/a> of AI like being a \u201csports car,\u201d but the problem for most jobs is they are built like New York City, full of traffic lights and gridlock. Have you ever driven in in Manhattan? \u201cWhat the hell are you doing with a sports car\u201d in that case? In the case of the calculator, he said, it took him about a month to build the prototype and four years to bring to the public, for reasons including legal review, grant submissions and interactions with the NIH. So essentially: paperwork.<\/p>\n

He\u2019s no Luddite. He credits AI with helping him translate statistical code across programming languages and build prototypes faster than he could alone. But his most irreplaceable function, he said, isn\u2019t running regressions. It\u2019s managing the human layer: communicating with a consortium of international surgical oncologists, from Yale to MD Anderson to the University of Toronto, specializing in cancers ranging from thoracic to orbital sarcomas, translating between their clinical instincts and the demands of statistical rigor.<\/p>\n

\u201cTheir lives are such that if I get 15 minutes a day with them, that\u2019s extremely lucky. So I need to make everything as precise and concise as possible.\u201d No AI, he added, could replicate the register that relationship requires. Even the approved use case, writing email, would be missing the key relational aspect. \u201cActually creating the prototype, and I think you\u2019ve heard this before, create using AI to create a prototype is fantastic. But once you try to get from prototype to scale, it kind of hits all of these roadblocks of red tape and bureaucracy and committees.\u201d<\/p>\n

That is exactly the kind of work Imas has in mind\u2014not performance, not artistry, but the irreducibly human judgment that holds complex institutions together.<\/p>\n

The speed problem<\/p>\n

Imas hasn\u2019t abandoned his fears. His optimistic scenario depends entirely on the pace of transition. If the shift from commodity economy to relational economy happens gradually, history suggests the labor market can absorb and adapt. But if AI automation accelerates faster than workers and institutions can retrain and reallocate, the demand-collapse scenario he spent years warning about remains entirely on the table. <\/p>\n

\u201cThe speed of change really matters,\u201d he said, \u201cwhether we get to this hopeful version versus the more worrisome one.\u201d<\/p>\n

Imas warned that people who are still skeptical of AI as overblown hype are fooling themselves, likely because they\u2019re using a chatbot model from years ago, not a frontier model. \u201cThese two things should not be categorized in the same bucket of technology,\u201d he argued, saying that that AI is still very \u201cjagged,\u201d an increasingly popular term for thinking about AI\u2019s probabilistic nature and tendency to hallucinate. \u201cBut it\u2019s going to be jagged in the sense of, at some point, the valleys are going to be very, very high \u2026 even the low points are going to be very impressive.\u201d<\/p>\n

Morgan Stanley warned in its March research note that AI disruption was \u201cbecoming more acute as LLM capabilities increase at a more rapid rate than expected,\u201d flagging the potential for large-scale workforce reductions across industries. The gap between that projection and a cancer statistician quietly waiting for the enterprise ChatGPT enthusiasm to blow over captures exactly the uncertainty Imas, despite his hard-won optimism, still can\u2019t fully resolve.<\/p>\n

Imas said he was still \u201cworried about\u201d people who are sticking their heads in the sand about AI: \u201cMy primary role right now is to sit people down one on one and get them trained on top-flight technology.\u201d He said he sees his relational aspect theory as both plausible and positive, \u201cbut it took me a long time to get to it.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"Alex Imas didn\u2019t arrive at optimism easily. The University of Chicago economist economist occupies an unusual space in…\n","protected":false},"author":2,"featured_media":387403,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[365,363,364,22048,111,139,69,624,145],"class_list":{"0":"post-387402","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-disruption","12":"tag-new-zealand","13":"tag-newzealand","14":"tag-nz","15":"tag-productivity","16":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts\/387402","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/comments?post=387402"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts\/387402\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/media\/387403"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/media?parent=387402"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/categories?post=387402"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/tags?post=387402"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}