Nobel Prize-winning economist sounds the alarm: when AI no longer empowers human beings, the "phantom economy" will devour everything.

Nobel laureate in economics Daron Acemoglu warned that multiple factors are driving artificial intelligence to transform human society in a "labor-replacing-oriented" model, the so-called "AI disrupts everything" will eventually replace humans, and may bring serious irreversible consequences to social order. This latest view from the Nobel laureate can be seen as a comprehensive response to Citrini Researchs blockbuster prediction of the 2028 AI doomsday, which foresees a dystopian AI future shaped by artificial intelligence, predicting that while global AI productivity will soar beyond expectations in 2028, the complete disruption of white-collar employment will lead to a "global economic epidemic." Although news headlines, hype in the tech industry, and employers all suggest that a near-term super revolution of artificial intelligence that will make workers more efficient and successful is on the horizon, Acemoglu, in a recent media interview, offered a more restrained and unsettling negative view. He agreed that recent developments, especially in the advancement of AI technology focused on "agentic AI-powered workflow", progress faster than he personally expected; but when it comes to reliability, reasoning ability, and understanding of the real world, he believes that today's AI systems still have shortcomings; he said that this implies that any breakthrough that would bring about broad and immediate revolutionary changes in business productivity is unlikely in the short term. However, the uncertainty of where the future is headed is much higher than during any previous technological revolution period. Acemoglu warns that tech giants overwhelmingly focus on replacing laborers on a massive scale with AI, rather than forming positive complementarity with workers. Acemoglu says this approach could lead to a false prosperity of "Ghost GDP," or severe social consequences. He believes that the greatest economic benefits will come from "pro-laborer AI" - a paradigm of AI technology development that enhances human capabilities, enabling workers to perform more complex, higher-value tasks. He stated that current business incentives, market structures, and policy frameworks all lean towards labor replacement. Without a change in direction, he warned that large-scale job replacement - especially among the global white-collar workforce, could put unprecedented pressure on the labor market, significantly depress worker wages, and disrupt the stability of human societal institutions. Acemoglu's view on the economic disaster that massive job displacement by AI could bring aligns perfectly with Citrini Research. Citrini Research's latest "AI prosperity crisis" mechanism chain is: AI agent-based intelligent entities lead to the replacement of white-collar jobs, resulting in wages and consumption power declining, ultimately leading to the emergence of "Ghost GDP" where GDP and productivity data continue to grow, but the human consumption engine, which accounts for about 70% of GDP, falters, presenting a "false prosperity without consumption"; under this "dystopian" mechanism, the economy, traditionally driven by human consumption, is eroded, causing risk assets like stocks to experience negative feedback at their peak, even leading to unemployment rates surging into double digits, ultimately resulting in a "retrospective disaster narrative" of global stock markets drastically retreating from their highs. Citrini Research splits the single-line story of "AI = productivity / profit rate increase" hard into the conflict of "market prosperity vs real economic weakness." Acemoglu also emphasized that shaping the trajectory of AI development requires both public discussion and intervention from governments globally. He criticized the grand narrative logic of tech giants' "AI competition," stating that such purely virtual competition narratives are misleading and may harm employment and economic growth; instead, he advocates for a broader focus on actual applications that can improve human life expectancy and productivity in sectors like healthcare and manufacturing. A Nobel laureate committed to advancing institutions from abstract narratives to comparable economic objects Daron Acemoglu, who won the Nobel Prize in Economics in 2024 with Simon Johnson and James A. Robinson, for his core achievement in studying how institutions are formed and how they affect economic prosperity. This definition is crucial because it proves that Acemoglu's award was not due to a single growth model or a particular local theory, but rather because he systematically advanced the grand question of "why are some countries wealthy and others poor" to the empirical forefront of institutional economics and political economy. His most essential contribution to the field of economics can be summarized in one sentence: turning "institutions" from abstract narratives into recognizable, comparable, and causally analyzable economic objects. According to official MIT information, his research areas include macroeconomics, political economy, labor economics, development economics, and economic theory. His representative work further extends to areas such as technological change, automation and employment, wage inequality, democracy and growth, network shocks, environmental and directional technological transition. It is also for this reason that Acemoglu is currently receiving increased attention from investors in the financial markets, with his remarks potentially influencing the direction of stock market investments. Investors believe that his academic background suggests he can analyze how AI, Siasun Robot&Automation, and automation may reshape future productivity, job structures, and income distribution within the frameworks of macroeconomics, labor, and technology. AI may indeed disrupt everything, including human society as a whole Since the beginning of this year, the pessimistic narrative of "AI disrupts everything" has gained momentum, and economists, including Nobel laureate Daron Acemoglu, are increasingly concerned that this disruptive effect may lead to the collapse of civilization and order due to high unemployment, false prosperity in productivity, and elements of an "Ghost GDP" economic epidemic accelerating together. The pessimistic tone of "AI disrupts everything" since February is mainly due to the market's growing concerns that the AI agent workflow, exemplified by companies like Claude Cowork and OpenClaw (formerly known as Clawdbot and Moltbot), which have been blazing and spread virally, may weaken the entire software empire based on the SaaS seat subscription revenue model, leading to a rare sell-off. This sell-off quickly spread to industries such as insurance, real estate, trucking, and any other industries that rely on seat revenue models or labor-intensive business models - the market believes that these industries will be completely disrupted by AI. Not only the US stocks, but the global stock market's software sector has been continuously hit hard in the panic of "AI disrupts everything" since February, despite the surge in buybacks of software stocks in the US, investors are not buying it because the market is truly concerned whether long-term fundamentals and business models will be completely reshaped by AI entities like Claude Cowork and OpenClaw. The "Anthropic storm" that has devastated software stocks is still fermenting in global stock markets, and this wave of sell-offs has accelerated to traditional industries such as wealth consulting and management, as well as real estate consulting, which appear to be on the brink of being completely disrupted by AI. The market's pessimistic expectations of "AI disrupts everything" have hit various industry sectors like a domino effect, causing a rotation of declines from software, SaaS, PE to insurance, traditional investment banking, wealth management, real estate, property management, and even logistics sectors. AI has been sweeping through each traditional industry in the past three to four weeks, with investors accelerating the sell-off of potential "losers." Acemoglu's latest view and Citrini Research's "2028 AI doomsday prediction" focus on the mainstream path of AI technology updates increasingly leaning towards "replacing labor" rather than "enhancing labor" in the current business incentives, preferences in capital markets, and policy frameworks. Citrini offers a stress test-style doomsday scenario, while Acemoglu provides a warning in the context of institutional economics if the AI technology route continues to be solely driven by maximizing capital returns, it may lead to a series of income and distribution shocks rather than efficiency dividends or prosperity in productivity. Citrini Research's research report, which the market refers to as the "2028 AI doomsday prediction," has caused significant fluctuations not because of how many "new facts" it presents, but because it offers a structurally complete and tradable scenario: it presents a counterintuitive proposition in the form of a "macro memo looking back at June 2028" - "If the AI bull market narrative continues to be proven correct, will it actually be bearish for the economy and markets?" Indeed, AI in the future has the potential to create a "localized dystopian-style" economic shock, but the "global economic epidemic" is not the baseline scenario, but a left tail risk that requires multiple conditions to go out of control simultaneously. IMF forecasts show that about 60% of jobs in advanced economies may be impacted by AI, with approximately half potentially leading to productivity enhancement, while the other half is closer to decreases in labor demand and stagnant productivity; the World Economic Forum indicates that 40% of employers expect to cut jobs in tasks that can be automated by AI, but by 2030, AI and information processing technologies combined may still create 11 million jobs while replacing 9 million jobs. Anthropic's latest labor research also found that the most exposed professions currently include programmers, customer service representatives, and financial analysts, but there has been no significant increase in unemployment rates in these professions so far; there has only been a slight slowdown in recruitment for young people aged 22 to 25. In other words, the most immediate risk is not "mass unemployment tomorrow," but rather the erosion of white-collar, entry-level, and high-skilled high-income service industry entrance positions, which then transmit through wages, consumption, and social mobility to the macroeconomic level. Economists, including Acemoglu, repeatedly emphasize that the trajectory of AI can be shaped: government procurement, novel tax design under the AI era, competition policies, intellectual property arrangements, vocational training and redistribution mechanisms will all determine whether AI will be built as a "substitute for humans" or as a "reinforcement of the human system." Acemoglu states that whether AI will evolve into an economic epidemic depends on whether we build it as a "for humans system" or a "strengthening of the human system."