From statistical physics to social sciences: the pitfalls of multi-disciplinarity
作者反思跨学科研究的困难，指出统计物理对社会科学的主要贡献是揭示个体层面不存在的涌现行为，如危机、恐慌、舆论反转等，并强调基于主体的模型是解释这些现象的有力工具。
Abstract This is an adapted version of my inaugural lecture at Collège de France in 2021. I reflect on the difficulty of multi-disciplinary research, which often hinges on unexpected epistemological and methodological differences, for example, about the scientific status of models. What is the purpose of a model? What are we ultimately trying to establish: rigorous theorems or ad hoc calculation recipes; absolute truth, or heuristic representations of the world? I argue that the main contribution of statistical physics to social and economic sciences is to make us realize that unexpected behavior can emerge at the aggregate level, which isolated individuals would never experience. Not only crises, panics, opinion reversals, the spread of rumors or beliefs, fashion effects, and the zeitgeist but also the existence of money, lasting institutions, social norms, and stable societies must be understood in terms of collective belief and/or trust, self-sustained by interactions, or on the contrary, the rapid collapse of this belief or trust. Agent-based models provide a powerful and natural framework to account for such phenomena.