Thermodynamics, Infodynamics and Emergence

Abstract

Emergence of novel processes, properties, structures, and systems is a poorly understood phenomenon. Emergence, information and energy are interrelated properties of nature: it takes free energy (energy that produces work, designed as F) to acquire information, and it takes information to increment free energy. Useful information (Φ), is the one that increases free energy, and differs from information not producing free energy or producing entropy. Energy obeys all laws of thermodynamics, while information may not. When energy and information of systems interact, novel properties or levels of energy and information may emerge. Information can reveal itself in different forms (as entropy, order, complexity, physically encoded, mechanical, biological, structural, in neural or social networks, etc.). Information may increase free energy by reducing entropy in an open system, or by capturing free energy from the surroundings. The dynamics of information and energy has been studied mostly in physical-chemistry and engineering. Now we find it everywhere, including in computer sciences, genetics, biotechnology, experimental social sciences, and experimental law. In emergent systems new possibilities of increasing free energy and useful information appear. Emergent complexity is visible in the transitions from subatomic particles to atoms, from atoms to molecules, to cells, to organisms, to societies and ecosystems. A law for irreversible thermodynamics stating that ΔF ~ ΔΦ, is evidenced empirically in all these levels of complexity, confirming that INCREASES IN USEFUL INFORMATION AND INCREMENTS IN FREE ENERGY ARE COUPLED. As free energy helps access more information, and more information produces more free energy, evolution by natural selection accumulates ever more useful information, giving birth to life. In contrast, increases in entropy decreases free energy and might affect the amount of useful information available in the system. More noise or misleading information decreases useful information which decreases free energy. These relationships help us understand the evolution of life, societies, ecosystems, and autonomous artificial life. Quantifying concomitant changes in energy and information is needed to understand the relationship between them. The endeavor to achieve this has begun (Jaffe 2023 [https://www.qeios.com/read/2VWCJG.5]).