Instability and Information

TL;DR

This paper explores how systems adapting to information can produce extreme, self-similar events, revealing that local minimization of fluctuations can paradoxically increase global instability across various domains.

Contribution

It uncovers a unifying principle linking stability and instability in complex adaptive systems, supported by models and behavioral experiments.

Findings

Self-similar bursts of activity emerge from first principles.

Minimizing local fluctuations can heighten sensitivity to perturbations.

The principle explains phenomena in balancing tasks and financial markets.

Abstract

Many complex systems exhibit extreme events far more often than expected for a normal distribution. This work examines how self-similar bursts of activity across several orders of magnitude can emerge from first principles in systems that adapt to information. Surprising connections are found between two apparently unrelated research topics: hand-eye coordination in balancing tasks and speculative trading in financial markets. Seemingly paradoxically, locally minimising fluctuations can increase a dynamical system's sensitivity to unpredictable perturbations and thereby facilitate global catastrophes. This general principle is studied in several domain-specific models and in behavioural experiments. It explains many findings in both fields and resolves an apparent antinomy: the coexistence of stabilising control or market efficiency and perpetual instabilities resembling critical phenomena in physical systems.