Ross McKenzie's 187-page review explores emergence across physics, biology, and AI

Ross H. McKenzie's monumental review, "Emergence: from physics to biology, sociology, and computer science," (arXiv:2508.08548v4) provides a sweeping 187-page, 474-reference analysis of how complex systems produce novel properties. Defining emergence as properties of the whole that individual parts lack, the paper explores universality, order, unpredictability, and self-organization across disciplines including condensed matter physics, neural networks, protein folding, and social segregation. McKenzie argues that a key challenge is bridging macroscopic emergent phenomena with microscopic interactions, proposing that intermediate mesoscopic scales—where new weakly-interacting entities appear—are essential. He champions toy models like the Ising model as vital tools for understanding emergence, and discusses effective theories for describing phenomena at specific scales.

The revised version (v4, updated July 2026) expands significantly on three areas: molecular structure, quantitative measures of causal emergence, and biological evolution. McKenzie contends that an emergent perspective should reshape scientific strategy—influencing research questions, methodologies, and resource allocation. The ultimate, elusive goal is the design and control of emergent properties. This comprehensive work serves as both a foundational reference for complexity science and a call to action for researchers to adopt emergent thinking across physics, biology, sociology, and AI. Its interdisciplinary scope makes it particularly relevant to AI developers dealing with emergent behaviors in large language models and multi-agent systems.