What Emergence Can Possibly Mean (2410.15468v1)

Abstract: We consider emergence from the perspective of dynamics: states of a system evolving with time. We focus on the role of a decomposition of wholes into parts, and attempt to characterize relationships between levels without reference to whether higher-level properties are "novel" or "unexpected." We offer a classification of different varieties of emergence, with and without new ontological elements at higher levels.

• The paper presents a taxonomy that categorizes emergence into four types by analyzing system decomposition and micro-macro dynamics.
• It employs a dynamics-based methodology to clarify how local interactions and nonlocal correlations give rise to distinct emergent behaviors across various fields.
• The framework offers practical insights for computational modeling and interdisciplinary research, enhancing our understanding of complex systems.

Emergence: Dynamics and Decomposition

The paper "What Emergence Can Possibly Mean" by Sean M. Carroll and Achyth Parola offers an analytical perspective on the concept of emergence, particularly focusing on the dynamics of systems and the roles of decomposition into subsystems. This piece does not prioritize the novelty or unpredictability of emergent properties, instead proposing a structured taxonomy of emergence, framed in the context of system dynamics and level relationships.

Overview of Emergence Taxonomy

The authors propose a classification system for emergence that hinges on the relationship between micro and macro-level descriptions of systems, particularly emphasizing the decomposition of systems into parts. Their framework is deliberately designed to move away from subjective interpretations of novelty typically associated with emergence, proposing more objective, dynamics-based criteria.

The taxonomy includes four main types of emergence:

1. Type-0 (Featureless) Emergence: This form does not rely on subsystem decomposition and involves systems where a macro theory is a coarse-grained version of a micro theory that can still predict system behavior in a compatible way with time evolution. Classical mechanics emerging from quantum mechanics under certain conditions serves as an example.
2. Type-1 (Local) Emergence: Here, macro-level subsystems are collections of micro-level subsystems, supporting more traditional views of emergence. Fluid dynamics emerging from molecular interactions offers a canonical instance. Complexity of emergence maps further delineates these into:
   • Type-1a (Direct) Emergence: Characterized by simple emergence maps, such as center-of-mass dynamics.
   • Type-1b (Incompressible) Emergence: Involves complex emergence maps, noted by higher-level unpredictability as seen in phenomena like Conway's Game of Life.
3. Type-2 (Nonlocal) Emergence: This type highlights macrosystems not confined to spatial locality, often observed in biology and social science domains, where global behaviors are not reducible to local interactions. This form is crucial when macro entities or causal actions appear nonlocal from a micro point of view.
4. Type-3 (Augmented) Emergence: Closely aligned with strong emergence, it introduces new ontological elements absent in lower levels. Here, macro-level entities possess properties and influences that do not simply supervene on micro-level entities, potentially relevant in discussions surrounding consciousness or life origins.

Implications and Future Directions

The paper contends that emergence is not merely an artifact of limited human understanding but can be characterized by tangible relations between system levels. It emphasizes that while strong emergence poses conceptual challenges, particularly with respect to causal closure, identifying clear criteria through their taxonomy can aid in understanding complex systems.

Practically, this classification can facilitate more precise discourse in cross-disciplinary studies employing emergence, such as cognitive science, social dynamics, and complex systems. The distinction between different types of emergence based on system dynamics provides a robust framework that could influence both theoretical research and enhancement of computational models simulating emergent phenomena.

The paper suggests that broad applications of this taxonomy in philosophical and applied contexts could refine our understanding of emergence. Future research might explore computational approaches to approximate the complexity of the emergence map or investigate real-world systems that exemplify nonlocal and augmented emergent behaviors.

In synthesis, Carroll and Parola's framework offers a rigorous approach to emergence, shifting focus from emergent properties' unpredictability to a structured analysis grounded in system dynamics and decomposition, and thereby enriching the philosophical and scientific discourse on the nature of complex systems.