Global Systems Science
Policy is the art of achieving a desired outcome in the presence of constraints and differing priorities. It is largely a coordination problem, and data and systems models can help investigate policy options.
For example, the Ebola outbreak in West Africa did not spread worldwide because science-based policies were implemented, replacing ineffective policies such as restricting movement by closing borders.
The science of epidemics is one of the successes of Global Systems Science – an interdisciplinary approach to modelling the complex, multi-faceted and intertwined problems of the modern world. Another example is the use of network science in financial regulation dealing with many interconnected financial actors.
As its name suggests, most of those problems have a global context, but Global Systems Science addresses policy issues at all levels – from the individual to local communities to nations to regions.
There are four main elements in Global Systems Science:
Policy at all levels, from individuals to the world: policy problems exist at global, national and local scales. How can these problems be tackled? How can it be known which, if any, proposed policy options will work?
The new, interdisciplinary approach: we will explore how the science of complex social, economic, political, biological, physical and environmental systems can inform policy makers in their work.
Data science and computational modelling for policy makers: this “policy informatics” involves new, policy-oriented methods of modelling complex systems on computers.
Citizen engagement: a central concept of GSS is that the behaviour of social systems emerges bottom-up, from the interactions of individuals and institutions, in the context of top-down policy constraints. Individual citizens must be involved in decision making and policy formulation if policies are to work.
Global Systems Science provides a prescription for applying systems thinking and complex systems science in policy.