DOI
DOI 10.1007/978-3-319-42424-8_14

Summary
This publication presents the main aspects of Global Systems Science (GSS), an emerging and transdisciplinary field of study that aims to model social, economic, political and environmental systems in order to provide substantial support for the design of effective policies. As the first sentence of the chapter affirms: “the vision of Global Systems Science (GSS) is to provide scientific evidence to support policy-making, public action and to enable civil society to collectively engage in societal action”. According to the authors, GSS may:
- Help developing an integrated policy perspective on global challenges
- Develop a research agenda to tackle the fundamental research challenges
To reach its objectives, GSS makes use of complex system science to represent the world and understand how it changes. This field makes use of Agent-Based Modelling (ABM) as an instrument to represents possible outcomes emerging from the establishment of a new policy. Differently from traditional theories and methods of analysis (e.g. “rational choice theory”), GSS does not aim to reach an optimal equilibrium, as it incorporates the perspective that no prediction is perfect. Thus, rather than elaborating the “right policy”, GSS tries to establish the policy that is “more likely to reach the best outcome”. In doing so, GSS takes into account the “narratives” spread among people. Since “narratives provide the structure by which individuals understand the world, in which they live”, they are also included in GSS models, which gives a quite active role to citizens, abandoning the “top-down approach”.

Relevance for Complex Systems Knowledge
The paper directly deals with issues of complexity and interdisciplinarity by presenting a whole field of analysis including both of them. The article is relevant for reimagining and improving higher education, as it also presents clear examples of how GSS might be used and why it should be adopted. Limitations of traditional methods of analysis for policy making are clearly presented, as well as the issues that GSS methodology overcomes:
- Unreliability of point prediction
- Unpredictability of extreme events
- Emergence of unintended consequences
- Absence of definitive predictions
Regarding interdisciplinarity, the article elaborates a clear cooperation between social scientists and computer scientists, which, together, are supposed to join forces in order to establish the models that will later be used to inform policy makers and citizens. By incorporating computer modelling, social models and social constructs (“narratives”), GSS aims to maximize its reliability and adherence to reality.

Point of Strength
- It provides clear examples of complex social systems
- It establishes a clear distinction of roles between social scientists and expert of complex systems science
- It directly deals with global issues (e.g. climate change)
- It adopts a bottom-up approach
- It presents the advantages of complex systems perspective in comparison to traditional models