FYS: The Economics of Hidden Truth

3 Credits.

How do economists measure GDP from outer space? How do we uncover latent variables in machine learning and AI? What if you were never free to make your own choices? Drawing on both lived experience and academic research, this seminar examines the relationship between data, ideology, human behavior, and unobservable truth—with the U.S. and China as comparative anchors. Students will explore contrasts between education systems; the economic, social, and historical consequences of the Cultural Revolution and One-Child Policy; the meaning of human rights and individual freedom; and the challenges of interpreting information where data may be incomplete, manipulated, or hidden.Along the way, students will learn modern technologies and econometric methods used to uncover "latent" information—from satellite imagery and nighttime lights measuring economic activity, to identifying hidden information in human decision-making, to understanding how latent-variable methods power machine learning, AI, robotics, and self-driving systems. No prior background in statistics is required.Ultimately, the course invites students to reflect on their own unobservable truth—their values, ambitions, and sense of purpose. Rather than offering definitive answers, it models an enduring pursuit of truth in a world where much of what matters remains hidden, uncertain, or imperfectly measured.