Information thinking: the transformation of complexity and scientific thinking - Wu, Tianqi; Zhang, Haisha; Wu, Kun (Frontiers in Psychology, 2025)
Diverse interpretations of the fundamental nature of the world and its evolutionary patterns have shaped multiple paradigms of scientific and philosophical thinking. At the micro level, ontological understandings have evolved from the ancient Greek atomic theory to modern conceptions based on dynamic energy fields. At the macro level, the comprehension of evolutionary mechanisms has shifted from a teleological model of cosmic evolution to one characterized by bifurcation and chaos in complex systems. The epistemological framework that holds the world to be composed of immutable, indivisible particles with static mass is referred to as “substance thinking,” whereas the view that the world consists of variable, massless energy fields is termed “energy thinking.” While teleological thinking emphasizes stability and simplicity in macro-level evolutionary outcomes, bifurcation and chaos thinking highlights the variability and complexity inherent in such processes. Across both foundational constituents and evolutionary models, scientific cognition has demonstrated a clear transition from simplicity to complexity, thereby driving a paradigm shift in scientific thinking from simplicity-oriented to complexity-oriented approaches. However, the intrinsic multidimensionality and non-linearity of complexity render it incommensurable with any single or limited set of dimensional metrics. The dialectical integration of micro-level randomness, variability, and interaction with macro-level emergence and constructive dynamics may represent the core feature of complexity. On this basis, informational thinking—grounded in the theoretical framework of information philosophy—emerges as a cognitive paradigm that interprets the essence of phenomena through structural, relational, and processual dimensions. By means of symbolic representation, it reveals the historical states, operative mechanisms, and prospective trajectories of systems, thereby offering a novel theoretical dimension—both holographic and integrative—for the advancement of complexity studies.