Global systems science

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Global systems science (GSS) is a discipline that aims to help policy making in complex situations. It is closely related but not equal to systems science which is a much broader set of disciplines (e.g. operations research, systems biology, chaos theory, systems theory, and systems engineering) and is not necessarily related to policy making. GSS is described in a book chapter[1] and on an online course] by FutureLearn.

The main ideas included in global systems science are

  • understanding the society as a system of micro- meta- and macro-level systems,
  • including citizens as key participants in policy processes to inform about and implement micro-level issues,
  • using rich datasets such as big data to understand the dynamics of systems and develop evidence-based policy[2],
  • to view policy-making as taking iterative actions and adjusting them according to the responses achieved.

Global Systems Science addresses the policy dilemma: how can policy makers choose between policy options, and be confident that their policies will have the desired outcomes and won’t have undesirable outcomes? Because of this dilemma, it is important to consider unintended consequences (such as increasing biofuels competing with food production[3]) and the tragedy of the commons[4].

Policy has two sides. The first is normative, making the world as it ought to be. The second is technical: given that it has been decided how the world ought to be, how can this be achieved?

Global Systems Science has four main elements, as shown below.[5]

  1. Policy at all levels, from individuals to the world: How can we know which, if any, proposed policy options will work?
  2. The new, interdisciplinary approach: how the science of complex social, economic, political, biological, physical and environmental systems can inform policy makers in their work.
  3. Data science and computational modelling for policy makers: policy informatics provides new, policy-oriented methods of modelling complex systems on computers.
  4. 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.

Important topics can be better understood by using GSS include climate change[6][7], the Arab spring[8], global epidemics[9], city planning[10][11][12], digital markets[13]

The workflow and GSS's role in it is depicted in Figure 1.

Figure 1. Global systems science in a policy workflow.

A key objective of GSS is to provide information for the policy process. This includes syntheses of large-volume data from disperse sources[14].

Predicting future events based on current actions is one important aspect. However, few things can be predicted precisely like in physics. Some can be predicted with reasonable certainty, while especially some social phenomena are chaotic by nature and are extremely difficult or impossible to predict. This is because the system may have several feedback loops balancing or reinforcing small changes in initial conditions. Also, some events are so individual, rare, extreme, or unprecedented that it is not possible to make predictions based on their previous distributions. All this makes predictions useful [15]

According to GSS, predictions are difficult but useful when used with caution. Some conclusions:

  • point predictions are the exception in social systems
  • social systems are sensitive to initial conditions and hard to predict
  • some events in social systems cannot be replicated
  • some events are unprecedented
  • computer simulations give insights into what might happen
  • computer simulations can expose unknown unknowns.

In GSS, a system is defined in this way:[16][17]

  • an assembly of components, connected together in an organised way, where
  • the components are affected by being in the system and the behaviour of the system is changed if they leave it
  • the organised assembly of components does something, and
  • the assembly has been identifed as being of particular interest

In network systems, positive and negative feedback loops are important. Causal relationships between factors can be described as arrows pointing from a cause to an effect. A policy situation is typically a complex network of causes and effects, and these can be described using causal diagrams. A feedback loop exists when it is possible to follow these arrows and return to the origin. Such feedback may be balancing (the feedback tends to reduce changes in the original factor, making it stable) or reinforcing (the feedback tends to amplify changes in the original factor, making the system unstable). Stability is often a good thing for a policy situation, but not always. Balancing feedback loops may make it very difficult to turn away from a current devastating track. System dynamics is a discipline studing complex systems and their behaviour, including feedback.

Systems are often described as being on different levels, i.e. micro level (individuals), meso level (groups, organisations) and macro level (societies). Often it is necessary to consider all these levels simultaneously, because they may have causal links and feedback loops from one level to another, and the system cannot be guided when looking only one level.[18]

Policy design is an iterative process where decision makers set objectives and start planning for solutions. When planning proceeds and information accumulates, need for compromises occur and force to adjust plans and often objectives to match reality. In this process, what decision makers need and can achieve is distilled out of what they want.[19]

Humans are social animals and they strongly affect each other's behaviour. Therefore it is also important to understand socail networks and their effects on group behaviour and how action patterns spread in a population. People are closely connected to each other, as described by the "six degrees of separation" hypothesis.[20].

Policy informatics means the use of information and communications technologies to support policy. These can be computer programs, visualisations, use of big data etc.

See also

  • Related FutureLearn courses:
  • Centre of Excellence of Global Systems Science (COEGSS) [15]. The Centre of Excellence for Global Systems Science – CoeGSS – provides advanced decision-support in the face of global challenges. It brings together the power of high-performance computing and some of the most promising thinking on global systems in order to improve decisions in business, politics and civil society.
  • Global Systems Science Portal (EU)
  • Global Systems Science Blog
  • Markus Müller. Who Owns the Internet? Ownership as a Legal Basis for American Control of the Internet. Fordham Intellectual Property, Media and Entertainment Law Journal Volume 15, Issue 3 2005 Article 2. [16]
  • The Glass-House Community Led Design is a national charity that supports communities, organisations and networks to work collaboratively on the design of buildings, open spaces, homes and neighbourhoods.
  • Xuemei Bai, Sander van der Leeuw, Karen O’Brien, Frans Berkhout, Frank Biermann, Eduardo S. Brondizio, Christophe Cudennec, John Dearing, Anantha Duraiappah, Marion Glaser, Andrew Revkin, Will Steffen, James Syvitski. Plausible and desirable futures in the Anthropocene: A new research agenda. Global Environmental Change. Volume 39, July 2016, Pages 351-362. doi:10.1016/j.gloenvcha.2015.09.017
  • Jeff Johnson, professor of complexity science and design at the Open University, Milton Keynes, UK.[17]
  • Complexity and global systems science course at ETH Zürich [18] with focus on Dirk Helbing's writings.
  • Collective Awareness Platforms for Sustainability and Social Innovation (organised by the European Commission) [19]

References

  1. ↑ Dum R., Johnson J. (2017) Global Systems Science and Policy. (pages 209-225) In: Johnson J., Nowak A., Ormerod P., Rosewell B., Zhang YC. (eds) Non-Equilibrium Social Science and Policy. Understanding Complex Systems. Springer, Cham. doi:10.1007/978-3-319-42424-8_14 ISBN 978-3-319-42422-4 (print) ISBN 978-3-319-42424-8 (online).
  2. ↑ HM Government: What Works: evidence centres for social policy, 2013 [1]
  3. ↑ Kurt Kleiner. The backlash against biofuels. Nature Reports Climate Change, Published online: 12 December 2007 doi:10.1038/climate.2007.71
  4. ↑ Garrett Hardin, The Tragedy of the Commons, Science, 13 Dec 1968: Vol. 162, Issue 3859, pp. 1243-1248 doi:10.1126/science.162.3859.1243
  5. ↑ Two-week course about Global systems science in Futurelearn. [2]
  6. ↑ BBC News 22.12.2009. Why did Copenhagen fail to deliver a climate deal? [3]
  7. ↑ European Commission. Paris agreement. [4] Accessed 9.10.2017.
  8. ↑ Adam Roberts (15.12.2016). The Arab spring: why did things go so badly wrong? [5]
  9. ↑ Vittoria Colizza, Alain Barrat, Marc Barthelemy, and Alessandro Vespignani. The role of the airline transportation network in the prediction and predictability of global epidemics. [6] PNAS February 14, 2006 vol. 103 no. 7 2015–2020.
  10. ↑ Geoffrey West. The surprising math of cities and corporations. TED Talk July 2011. [7]
  11. ↑ FutureLearn Online course: Smart Cities. Explore the role of technology and data in cities, and learn how you can participate in the creation of smart cities. [8]
  12. ↑ MK:Smart. Developing Milton Keynes area. (MK:Smart is a large collaborative initiative, partly funded by HEFCE (the Higher Education Funding Council for England) and led by The Open University, which is developing innovative solutions to support economic growth in Milton Keynes.)[9]
  13. ↑ European Commission: Digital single market and global systems science [10]
  14. ↑ Christopher L. Barrett, Stephen Eubank, Achla Marathe, Madhav V. Marathe, Zhengzheng Pan, Samarth Swarup. Information integration to support model-based policy informatics. The Innovation Journal: The Public Sector Innovation Journal, Volume 16(1), 2011 article 2.
  15. ↑ University of Exeter. Famous forecasting quotes.[11]
  16. ↑ Jeffrey Johnson, Joyce Fortune and Jane Bromley, Systems, Networks, and Policy, in Non-Equilirbrium Social Science, Johnson et al (eds), Springer, 2017, doi:10.1007/978-3-319-42424-8_8
  17. ↑ Russel L. Ackoff, Towards a system of system concepts. Management Science, Vol 17, No. 11, July 1971.
  18. ↑ Jane Merrick, NHS feels the strain as hospital bed-blocking by elderly patients hits record levels, The Independent, Sunday 22 March 2015.[12]
  19. ↑ Jeffrey Johnson, ‘Policy Design, Planning, and Management in Global Systems Science’, in Complex Systems Design & Management Asia, Editors: Michel-Alexandre Cardin, Daniel Krob, Pao Chuen Lui, Yang How Tan, Kristin Wood. 2014.[13]
  20. ↑ Duncan J. Watts* & Steven H. Strogatz, Collective dynamics of ‘small-world’ networks, Letters to Nature, Nature, Vol 393, 4 June 1998.[14]
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