Abstract
Political scientists have conventionally assumed that achieving democracy is a one-way ratchet. Only very recently has the question of “democratic backsliding” attracted any research attention. We argue that democratic instability is best understood with tools from complexity science. The explanatory power of complexity science arises from several features of complex systems. Their relevance in the context of democracy is discussed. Several policy recommendations are offered to help (re)stabilize current systems of representative democracy.
Introduction
The Economist recently identified 80 countries whose democracy score declined during the last decade, including the USA and some consolidated European democracies (The Economist Intelligence Unit, 2017). While the question of how democracies arise and how such rise can be facilitated has received much research attention, little is known as yet about how democracies destabilize.Footnote1 The conventional assumption amongst political scientists was that achieving democracy is a one-way ratchet. Only very recently has the question of “democratic backsliding” attracted any research attention (Waldner and Lust, 2018). We argue that insights from complexity science can facilitate the study of democratic processes and institutions and the design of stabilizing policies. The cross-disciplinary approach to political science that we advocate here rests on mathematical models of human societies, built with tools from statistical physics, dynamical systems, complex networks, and game theory (Wiesner et al., 2018). These tools allow scientists to focus on the salient features of the complex system at hand.