From Statistical Physics to Social Sciences: The Pitfalls of Multi-disciplinarity

TL;DR

The paper discusses the challenges of multi-disciplinary research, emphasizing how statistical physics offers insights into collective behaviors and emergent phenomena in social sciences, highlighting the importance of trust, beliefs, and interactions.

Contribution

It highlights the epistemological and methodological differences in multi-disciplinary research and underscores the role of statistical physics in understanding emergent social phenomena.

Findings

Emergent behaviors arise at the collective level, not seen in isolated individuals.

Social phenomena like crises and norms can be modeled as collective beliefs and trust.

Statistical physics reveals unexpected behaviors in social systems.

Abstract

This is the English version of my inaugural lecture at Coll\`ege de France in 2021, available at https://www.youtube.com/watch?v=bxktplKMhKU. I reflect on the difficulty of multi-disciplinary research, which often hinges of 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 realise that unexpected behaviour can emerge at the aggregate level, that isolated individuals would never experience. Crises, panics, opinion reversals, the spread of rumours 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. The Appendix contains my opening remarks to the workshop ``More is Different'', as a tribute to Phil Anderson.