Nobel laureate in economics sounded the alarm: when AI no longer empowers humanity, the "phantom economy" will devour everything.

Nobel Laureate in Economics Daron Acemoglu warns that multiple factors are driving artificial intelligence to transform human society in a "labor-replacing oriented" mode, the so-called "AI disrupts everything" that could eventually replace humans and may bring severe irreversible consequences to social order. This latest view from the Nobel laureate can be seen as a comprehensive response to the "2028 AI Doomsday Prophecy" released by Citrini Research, which triggered global financial market panic selling. The prophecy paints a comprehensive picture of a dystopian AI future shaped by artificial intelligence. It predicts that by 2028, despite global AI productivity skyrocketing beyond expectations, the complete disruption of white-collar employment will lead to a "global economic plague." Although news headlines, hype in the tech industry, and employers are hinting at an imminent super revolution of artificial intelligence that will make workers more efficient and successful in the short term, Acemoglu recently gave a more restrained and unsettling negative view in a media interview. He agrees that recent developments, especially in the field of artificial intelligence technology focusing on "AI agent-based omniscient workflow," have progressed faster than he personally expected. However, when it comes to reliability, reasoning abilities, and understanding of the real world, he believes that today's AI systems still have shortcomings. He states that this means that any breakthrough that brings about a broad and immediate transformation in business productivity is unlikely to occur in the short term. The uncertainty of where the future is heading is much higher than in any previous technological revolution period, Acemoglu warns. He states that tech giants overwhelmingly focus on using AI to replace labor rather than complementing labor. Acemoglu suggests that this approach could lead to a false prosperity called "Ghost GDP," also causing serious social consequences. He believes that the greatest economic benefit will come from "Pro-worker AI" - AI technologies that enhance human capabilities so that workers can perform more complex, high-value tasks. He states that current business incentives, market structures, and policy frameworks are more inclined towards labor replacement. If this direction is not changed, he warns that large-scale job substitution - especially among the global white-collar workforce - may put significant pressure on the labor market, drastically reduce worker salaries, and disrupt the stability of human social institutions. Acemoglu's view on the economic disaster that could result from widespread AI job substitution perfectly aligns with Citrini Research. Their latest "AI Prosperity Crisis" mechanism chain suggests that AI agent-based intelligent entities driving white-collar job replacement will lead to declining wages and purchasing power, ultimately resulting in a "Ghost GDP" scenario where GDP and productivity data continue to grow, but the engine driving 70% of human consumption stalls, leading to an "illusory prosperity without consumption." Under this "anti-utopian" mechanism, the economy driven by human consumption for a long time (as pointed out in the article with current high consumption rates) is eroded, causing risk assets like stocks to face negative feedback at high levels, and even leading to unemployment rates reaching double digits, resulting in a "retrospective" collapse of global stock markets from their highs. Acemoglu emphasizes the need for shaping the trajectory of AI development through public discourse and intervention at the global government policy level. He criticizes the grand narrative logic of tech giants' "AI competition," stating that such purely virtual competition narratives are misleading and could harm employment and economic growth. Instead, he advocates for a broader focus on practical applications in healthcare and manufacturing that can improve human lifespan and productivity. A Nobel laureate dedicated to advancing institutions from abstract narratives to measurable economic objects Daron Acemoglu, who won the Nobel Prize in Economics in 2024 with Simon Johnson and James A. Robinson, has core achievements in studying how institutions shape and influence economic prosperity. This definition is crucial because it proves that Acemoglu's award is not based on a single growth model or localized theory, but rather on his systemically advancing the grand question of "why nations are wealthy or poor" to the empirical frontier of institutional economics and political economics. His most core contribution in the field of economics can be summed up in one sentence: advancing "institutions" from abstract narratives to identifiable, comparable, and causally analyzable economic objects. According to official MIT materials, his research areas include macroeconomics, political economics, labor economics, development economics, and economic theory. His representative work extends further to areas such as technological change, automation and employment, wage inequality, democracy and growth, network impacts, environmental and directional technological transitions. It is for this reason that Acemoglu is particularly followed by investors in the financial markets today. His statements may even influence the direction of stock market investments, as investors believe that his academic background implies that he can analyze how AI, Siasun Robot&Automation, and automation will 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 not been well-received, and economists like Nobel laureate Acemoglu are increasingly concerned about the potential disruptive effects this may have on human society, such as high unemployment, false prosperity due to increased productivity, and the "Ghost GDP effect" causing economic plague elements to catalyze civilization and order to collapse. The pessimistic tone of "AI disrupts everything" since February mainly stems from the market's growing concern that AI agent workflows like Claude Cowork and OpenClaw (formerly known as Clawdbot and Moltbot) could undermine the entire software empire based on SaaS seat subscription revenue models. This rare selling pressure rapidly spread to industries such as insurance, real estate, truck transportation, and any other industries that appear to be based on seat revenue models or labor-intensive business models - the market believes that these industries will be completely disrupted by AI. Not only in the U.S. stock market, but the software sector of global stock markets has been continuously tumbling in the panic of "AI disrupts everything" since February. Despite the sharp increase in share buybacks in the U.S. software sector, investors are not buying it because what the market is truly worried about is whether long-term fundamentals and business models will be completely reshaped by AI intelligences like Claude Cowork and OpenClaw. The "Anthropic storm" that has hit software stocks is still fermenting in global stock markets, and this wave of selling is spreading to traditional industries such as wealth consulting and management, and real estate consulting that appear to be on the brink of being completely disrupted by AI. The market's pessimistic expectations of "AI disrupts everything" are impacting various industry sectors like dominos, causing software, SaaS, private equity, insurance, traditional investment banking, wealth management, real estate, property management, and even logistics sectors to experience "mutual collapse." AI has been sweeping through each traditional industry over the past three to four weeks, and investors are accelerating sales of potential "losers." Acemoglu's latest view and Citrini Research's "2028 AI Doomsday Prophecy" both focus on the mainstream path of AI technology updating and iterating, which is increasingly leaning towards "labor replacement" rather than "labor enhancement" under current business incentives, capital market preferences, and policy frameworks. Citrini provides a stress test-type doomsday scenario, while Acemoglu's warning serves as an institutional economic alarm. If the AI technology trajectory continues to be solely driven by maximizing capital returns, AI is likely to bring a series of income and distribution shocks rather than efficiency dividends or productivity prosperity. Citrini Research's study report, known as the "2028 AI Doomsday Prophecy," was able to cause fluctuations in a short period not because it provided many "new facts," but because it offered a structurally complete and tradeable left-tail scenario. By writing from the perspective of a "macro memorandum in June 2028," it poses a counter-intuitive proposition - "if the AI bull market narrative continues to be proven correct, will it negatively impact the economy and the markets?" Indeed, AI may create a "partially anti-utopian economic shock" in the future, but the "global economic plague" is not the benchmark scenario; it requires multiple conditions to simultaneously spiral out of control to become a left-tail risk. IMF forecast reports indicate that about 60% of jobs in advanced economies will be impacted by AI, but approximately half of those impacts may be productivity enhancements, while the other half are closer to declining labor demand and stagnant productivity; the World Economic Forum shows that 40% of employers expect to cut jobs at AI automatable tasks, but by 2030, AI and information processing technologies combined could still create 11 million jobs while replacing 9 million jobs. The latest workforce study by Anthropic also found that the most exposed occupations currently include programmers, customer service representatives, and financial analysts, but there is no significant increase in the unemployment rate for these occupations as of now; only a slight slowdown in hiring for young people aged 22 to 25 is observed. In other words, the most realistic risk at present is not "mass unemployment tomorrow," but rather the erosion of white-collar, entry-level positions, and high-education high-salary service industry roles, which will 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 in the AI era, competition policies, intellectual property arrangements, vocational training, and redistribution mechanisms will determine whether AI becomes an "expert capability enhancer" or a "wage suppression machine." Acemoglu states that whether AI evolves into an economic plague depends on whether it is built as a "system for people" or a "strengthening human system."