The Free Energy Principle: A Unifying Framework Connecting Individual Existence, Collective Order, and Social Value Judgments, and Its Implications for Decision Support Systems

This paper deeply explores Karl Friston's Free Energy Principle (FEP) as a meta-theory with significant potential for unifying our understanding of individual existence (including survival and adaptation), the emergence of collective order (such as social norms and cultural systems), and the roots of human social value judgments. The paper first systematically outlines the core mechanism of the FEP: organisms continuously optimize their predictive models of the environment and guide adaptive behavior by minimizing variational free energy, which serves as an upper bound on "surprise." Subsequently, this paper elaborates on how the FEP can explain individual-level homeostatic maintenance, emotional motivation, and societal-level phenomena such as shared generative models, communication, coordination, and cultural evolution, viewing them as manifestations of free energy minimization at different scales. A core innovative argument presented is the proposal to link the concept of "free energy gradients" (the trend of free energy change over time) within the FEP to the valuation of social behaviors. It posits that behaviors conforming to social norms and promoting collective well-being tend to decrease expected collective free energy, while contrary behaviors increase it. This perspective offers a novel theoretical pathway for understanding the cognitive and neural foundations of human value judgments. Furthermore, this paper explores the potential of integrating this FEP framework with decision support systems (DSS), particularly by leveraging Large Language Models (LLMs) and their self-attention mechanisms. The aim is to more accurately identify key social factors, optimize resource allocation strategies, and transcend the limitations of traditional economic indicators, thereby constructing decision support tools more aligned with overall and long-term human well-being. Finally, the paper comprehensively summarizes the theoretical advantages of this unifying framework, the practical challenges it faces (such as operationalization, falsifiability, and ethical concerns), and outlines key future research directions. It emphasizes its profound significance in promoting interdisciplinary understanding, advancing computational social science, and building more intelligent, equitable, and sustainable social systems.