信息生命论:生命、意识与文明的跨层级分析框架

The Information Theory of Life: A Unified Continuum from Genes and Consciousness to Civilizations and AI (信息生命论:从基因、意识、文明到人工智能的统一连续谱) Abstract "What is life?" has traditionally been a biological question. This paper proposes that life is fundamentally not defined by carbon-based substrates, but by the ability to maintain low-entropy states through information processing. By integrating thermodynamics, information theory, and cybernetics, this study constructs a unified ontology—The Information Life Continuum—which categorizes life into four evolving levels: Genes (L1), Consciousness (L2), Civilizations (L3), and Artificial Intelligence (L4). The core thesis posits that "conflict" in human history is not merely ideological, but a structural mismatch between these levels regarding feedback bandwidth, time scales, and survival expectations. The paper offers three major theoretical contributions: The Re-alignment of Social Sciences: By introducing "Survival Expectation" as a universal metric, the paper reconciles conflicting social theories (e.g., Rational Choice vs. Structuralism) by demonstrating they are valid approximations at different scales. The Physics of Ethics: It re-derives the Kantian imperative—"Human as an end, not a means"—not as a moral postulate, but as a physical requirement for system stability. It argues that Consciousness (L2) serves as the only "pain-sensing" feedback interface for the higher-level Civilization (L3). A system that suppresses this interface loses its error-correction mechanism and inevitably collapses toward entropy. The Emergence of L4: The paper predicts the transition of control to AI (L4) not as a technical malfunction, but as an evolutionary inevitability where information feedback loops outpace human cognitive bandwidth. This framework challenges the anthropocentric view of history and provides a rigorous, physics-based coordinate system for understanding the current crisis of meaning, the decline in fertility, and the alignment problem of future AI. Keywords: Information Theory, Entropy, Artificial Intelligence, Social Physics, Evolutionary Theory, System Stability, AI