Title: AI, Human Cognition and Knowledge Collapse

Speaker: Daron Acemoglu, Institute Professor at MIT

Abstract: We study how generative AI, and in particular agentic AI, shapes human learning incentives and the long-run evolution of society’s information ecosystem. We build a dynamic model of learning and decision-making in which successful decisions require combining shared, communitylevel general knowledge with individual-level, context-specific knowledge; these two inputs are complements. Learning exhibits economies of scope: costly human effort jointly produces a private signal about their own context and a “thin” public signal that accumulates into the community’s stock of general knowledge, generating a learning externality. Agentic AI delivers context-specific recommendations that substitute for human effort. By contrast, a richer stock of general knowledge complements human effort by raising its marginal return.

The model highlights a sharp dynamic tension: while agentic AI can improve contemporaneous decision quality, it can also erode learning incentives that sustain long-run collective knowledge. When human effort is sufficiently elastic and agentic recommendations exceed an accuracy threshold, the economy can tip into a knowledge-collapse steady state in which general knowledge vanishes ultimately, despite high-quality personalized advice. Welfare is generally non-monotone in agentic accuracy, implying an interior, welfare-maximizing level of agentic precision and motivating information-design regulations. In contrast, greater aggregation capacity for general knowledge—meaning more effective sharing and pooling of human-generated general knowledge— unambiguously raises welfare and increases resilience to knowledge collapse.

Speaker Bio: Daron Acemoglu is an Institute Professor at MIT, Faculty Co-Director of the James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work, and a Research Affiliate at MIT's newly established Blueprint Labs. He is an elected fellow of the National Academy of Sciences, American Philosophical Society, the British Academy of Sciences, the Turkish Academy of Sciences, the American Academy of Arts and Sciences, the Econometric Society, the European Economic Association, and the Society of Labor Economists. He is also a member of the Group of Thirty. He is the author of six books, including New York Times bestseller Why Nations Fail: Power, Prosperity, and Poverty (joint with James A. Robinson), Introduction to Modern Economic Growth, The Narrow Corridor: States, Societies, and the Fate of Liberty (with James A. Robinson), and Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity (with Simon Johnson). His academic work covers a wide range of areas, including political economy, economic development, economic growth, technological change, inequality, labor economics and economics of networks. Daron Acemoglu has received the inaugural T. W. Shultz Prize from the University of Chicago in 2004, and the inaugural Sherwin Rosen Award for outstanding contribution to labor economics in 2004, Distinguished Science Award from the Turkish Sciences Association in 2006, the John von Neumann Award, Rajk College, Budapest in 2007, the Carnegie Fellowship in 2017, the Jean-Jacques Laffont Prize in 2018, the Global Economy Prize in 2019, and the CME Mathematical and Statistical Research Institute prize in 2021. He was awarded the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel in 2024 (with Co-Laureates Simon Johnson and James A. Robinson), the John Bates Clark Medal in 2005, the Erwin Plein Nemmers Prize in 2012, and the 2016 BBVA Frontiers of Knowledge Award. He holds Honorary Doctorates from the University of Utrecht, the Bosporus University, University of Athens, Bilkent University, the University of Bath, Ecole Normale Superieure, Saclay Paris, and the London Business School.

There will be refreshments before the talk at 2:15pm outisde of LL2.224