Systemic risk in complex systems: understanding the system based on the system’s adjacent becoming

While understanding systemic risk in complex systems has gained growing attention, less effort is often dedicated to understanding the system itself.  Particularly, the typology of complex systems and collapse mechanisms that are consistent across domains remains understudied. Hence, critical questions arise, such as what do we need to know about the system’s characteristics to predict systemwide collapse, identify leverage points, or design resilience interventions? What system properties allow knowledge gained from one system to be generalized to other taxonomically similar systems? What signals can be deduced from a few systems’ global parameters to determine whether a system is in a stable, unstable, or critical region of its adjacent becoming?"

 

Answering these questions requires determining the typology of complex systems, which enables the study of system-level behaviors independently of the specific details of individual agents. This leads to universality, facilitating the study of collapse mechanisms transferable to other typologically similar systems, thereby providing insight into systemic risk.

 

This presentation introduces a novel typology of complex systems based on the concept of “adjacent becoming,” drawing on works of Stuart Kaufmann, C.S. Holling, and Marten Scheffer, among others which have established the language of attractors, regime shifts, evolution, and panarchical resilience in complex systems. The System’s Adjacent Becoming (SAB) is what the system is positioned to become while appearing to be in a stable condition, i.e., potential for a critical transition in deep stability. Such a proximal transformation potential can be characterized by four interrelated components consisting of a) the system's location in phase space and proximity to the most accessible alternative attractors, b) the topography of the current boundary basin, c) the system's current momentum and energy state, and d) the prospective trajectory and regime that a transition to a given alternative attractor would induce. These four components collectively determine the SAB potential, and thus the likelihood and qualitative characteristics of an imminent regime shift.

 

To assess SAB, what system has, what system does, and what system could become are the critical questions.  For such an assessment, a SAB-informed typology would be the first step. Therefore, the four SAB components lead to types based on nine interconnected system variables: (1) micro-macro dynamic type; (2) state of information processing and memory capacity; (3) degree of teleonomic coherence across levels and panarchical organization; (4) degree of agent heterogeneity; (5) type and intensity of emergence; (6) functional and computational efficiency rate; (7) initial condition and presence of path dependency; (8) manifestation of critical slowing down indicators and bifurcation proximity signals and (9) the existing geometric attractor landscape. 

This SAB-informed typology is phenomenologic-mechanistic in nature, which helps to learn about the structural and dynamical signatures of critical transitions and the quality of the new becoming, offering a unified language for understanding how complex adaptive systems of any kind approach their adjacent becoming and what determines whether they persist, transform, or collapse. This framework remains theoretical with operationalization challenges; future work must advance toward measurable proxies for the nine categories to quantify SAB of real-world systems.