An overview of Global Systems Science
In this first week you have seen examples of global systems. The diagram below shows how science can support policy making.
Global Systems Science is concerned with the interface between science and policy, and tries to clarify how policy makers and scientists can best work together.
In general, policy makers are interested in getting things done, while scientists are concerned with developing new methods and theories. It is quite natural that scientists and policy makers should have different agendas, although some policy makers are also scientists and some scientists are also elected politicians.
On the left-hand side of the diagram citizens and politicians decide the policy objectives and constraints.
In the middle, policy makers generate and evaluate possible policies to achieve their objectives. This is where scientists can help. In particular scientists can help evaluate policy suggestions. In some cases this may involve building elaborate computer models to investigate possible policy outcomes. Scientists can also help generate policies by providing policy makers with computer tools to synthesise data and providing easily understood visualisations of policy outcomes.
Ideally, policy makers, scientists, and other stakeholders work together in the centre of the diagram. Sometimes during this process the stakeholders decide to revisit the objectives and constraints on the left in order to generate acceptable policies.
When acceptable policies have been formulated they are usually subject to further political processes as shown on the right of the diagram, as those politicians and citizens not involved in formulating the policy have their say.
Global Systems Science has four main elements, as shown below.
Policy at all levels, from individuals to the world: How can we know which, if any, proposed policy options will work?
The new, interdisciplinary approach: 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: policy informatics provides 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. The reflexive nature of social science – that predictions can change behaviour – means that individual citizens must be involved in decision making and policy formulation.
In Week 2 we will develop these ideas further. But first, move on to the next step to test what you’ve learned this week.
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