Category Archives: Global Systems Science

some random notes and thoughts from GSS conference

random notes from the GSS conference


Some quotes that characterise GSS very well

‘ICT will not lead to sustainability it will lead to behavioural change towards sustainability’. The role of technology cannot be to help make our unsustainable lifestyle sustainable; it has to be to help us change this lifestyle.

‘A research agenda of GSS should be driven by ‘Pasteur’s principle’; that it is global challenges (like global warming, energy crisis, financial crisis) that drive a highly ambitious research agenda in close connection with society. Scientists should not be in love with their models but with the eventual usefulness of them.

GSS should contribute via models and data and their dissemination to global reasoning on global challenges. 

‘Prediction’: What does it mean in a constantly branching world (no repeatable experiment)?  (‘You cannot buy Apple stock today at the price of 10 years ago’)

GSS should link the top-down and bottom-up aspects of governance and decision making in society. GSS should make use of institutions (they are of use in a society and evolved as something useful) and make use of citizen-driven initiatives.

Data are artefacts: They are created for use and their functionality is defined by usage

Data are social objects: They cannot be seen independently of their use

Simulation can be wrong: How to account for that in policy decisions? What to do with probabilistic results in policy decisions? What about lower and upper bounds of prediction?

At the core of GSS is an understanding what it means and how to interpret results of models and data analysis.

Software is doing what it is programmed to do not what it is supposed to do


Models and data: big, unstructured, and constantly growing. Cost per GB of data is going constantly down (see eg Human genome) and cost has shifted towards data analytics.

Data platforms on data form third world countries (most of data that could drive a GSS agenda are form developed countries)

Ocean of unstructured data: How to make sense of these data (need for data analytics is today more urgent than need for data gathering).

Data are as much numerical as procedural. In particular agent-based modelling strongly depends on procedural data.


Simulation should not be over interpreted  beyond their validity range. One has to understand underlying assumptions.

Need for model integration

‘Eternity of models and data’: How to ensure that models and data are usable in the future.  What about data (like Twitter) that cannot be stored?

Workshop on narratives

‘Narratives are a primary means for people to make sense of the world’

A very useful distinction regarding the use of ICT in narratives is to distinguish

ICT as a tool to analyse narratives – ICT as a tool to help create/form narratives

The analysis part includes ICT tools of analysing online media (blogs, twitter etc) in terms of expressions of public sentiment. The ICT tools here are semantic analysis, network analysis, Bayesian methods and more.

The use of I CT in creation of narratives includes data visualisation, games, use of online media to enhance messages etc. Often the use of ICT can be seen less as a means to create narratives but as a means to spread and enhance narratives (e.g. youtube).

WRT the use of narratives as a means to convey messages, there seems a strong feeling of possible abuse of narratives.  It might in the light of this fear be good to distinguish between prescriptive and descriptive narratives (or more highflying normative and ontological). That is narratives that are supposed to make clearer a concept and narratives as a means to incite to action.

Narratives are used in the linkage of decisions in society and models/data driven knowledge in several ways:

- condense the message form the findings of models and data analysis (at the risk of oversimplifying). This need to condense the message is related in part to the fact that there is little evidence that policy makers base their decisions regularly on existing data. Mainly probably because data are not presented to them in a way that would allow them to guide their decision.

-to help decisions makers navigate in uncertain situations, narratives as a form of heuristics.

-narratives as a tool for traders

-Narratives as a guiding principle of action within a community. Banking was mentioned and the fact that the banking narratives evolved over the years (from making a reasonable living towards making an insane amount of money) and is now becoming a societal narrative no longer restricted to banking profession.

Colin Harrisson:

Can we develop a science of cities and what is the role of GSS in cities planning.

What can ICT do to reduce energy consumption (it is more to that than putting sensors everywhere)

Workshop on global Markets

EC official from DG MARKT (the directorate General in charge among others of financial regulation) were present and (as should be the case in GSS) there needs were driving the discussion of a possible research agenda.

Their main immediate need is a better understanding of the highly entangled banking networks. Their suggestion is to develop a research programme that identifies  the data needed (and thereby would guide EC regulation on what data should be made obligatory to provide for banks) and based on this data allows EC to better understand banking networks (in particular in shadow banking and the networks of transfer of risks).

From this immediate need (responding to which would be a case in point for GSS) there could be more long-term agendas like better understanding the issue of trust in financial systems via agent models.



The astronomy/telescope metaphor was used to refer to
the coupling of a challenge, Policies for Global Systems
with an instrument New Tools in Computer Science:
Big Data, Simulation tools , Visualisation.

The Challenge and the Tools might not be sufficient;
if we carry on the metaphor, the success of 16/17th century Physics
was certainly made possible by Tycho Brahe, Galileo and Copernic,
but it was fully exploited by theoretists such as Kepler and Newton.
Thanks to theoretists, the discoveries in Astronomy were generalised
and transferred to the much larger domain covered by Mechanics.

Theory is an important part of our understanding of the world.
Theory does not necessarily imply a comprehensive new World vision,
such as Quantum Physics or Relativity.
But it certainly includes unifying concepts and new methods.
In the case of Complex systems, new concepts were for instance percolation,
avalanches and SOC, classification by attractors, classes of universality,
dynamical regimes and transitions…
while new methods include renormalisation, replicas, damage spreading
and Liapunov exponents, search and learning algorithms.

GSS needs not only tools but also Theory.

Workshops on Global Markets

Two small workshops on global markets and sustainability



Objects of governance have turned into parts of a globally interconnected system whose sustainability is at risk. This calls for a « global systems science», which could on the one hand support governance and, on the other hand, explicit how power and influence are transmitted in these interconnected systems. The aim of this workshop is to investigate how those two issues materialize in the economic realm: new questions and challenges economic policy addresses to science and new questions and challenges science faces when investigating economic policy and decision making in a globalized market environment.


Middle-term issues, whose time-span approximately coincides with the average five years electoral mandate, might possibly be dealt with by neo-classical social science: policy-makers maximize their probability of being reelected by putting in place policies whose efficiency (number of jobs created or quantity of pollution avoided) can be assessed “all other things being equal” using computable general equilibrium models.  Questions about sustainability are of a different kind, they are not asked “ceteris paribus” as they rely on endogenous dynamics and challenge the very existence of the system under investigation.


Sustainability mainly refers to the long-term balance between economic development and environmental conservation but also materializes as problems with very short time-horizons such as the 2011 earthquake in Japan, the failure of Lehman brothers, or the sovereign debt crisis in the Eurozone. Both for short and long-term issues, decision-makers turn to science with very specific as well with very general questions, with micro and macro problems. As far as environmental change is concerned, questions range from “How to reproduce locally an industrial symbiosis like this of Kalundborg ?”  to “How to move to a competitive low carbon economy in 2050 ?” Turning to the financial realm, one might wonder whether (or until when) the global financial system was sustainable or if it can today provide the 30 billions euros Greece needs by 2020 to upgrade its energy system[1] ?


It is doubtful that a single model might address those issues.  Even if one embeds all existing heterodoxies, very few of the policy-relevant questions of the time can be answered. Among the challenges to be faced in order to overcome this failure are the disaggregation and the extension to non-equilibrium phenomena of economic models and the exploitation of the wealth of data at hands thanks to the IT revolution.


The burgeoning mind of economists has managed to develop a wide taxonomy of models (e.g general equilibrium, CAPM, Bertrand or Cournot competition, principal-agent) under the, most often ad-hoc, constraint of only considering equilibrium situations. There is little doubt that this taxonomy can be extended if the economist toolbox is enriched by non-equilibrium models inspired by harder sciences.  How to foster this process ? For example how can econophysics and agent-based models become mainstream within the economic profession ? Which standards can be established to better communicate about models that aren’t always analytically tractable ?


New classes of models and new tools are also required to exploit the wealth of data at hands thanks to the IT revolution. Statistical institutes produce a limited and rather immutable class of indicators with a certain lag. Now, most if not all the data collected by statistical institutes during census operations are in fact readily available in some electronic form and circulating at extremely high speed on the internet. What are ethical and methodological issues posed by “big data” ?  Are current models up to the challenge of parsing if not explaining  the material ?



Finally, as a counterpart to the questions posed by policy, shouldn’t global systems science come with series of interrogations about power and governance in the globalized economy ? With markets’ liberalization and globalization, nation states seem to have lost part of the influence and the power they had on the economy. Where has this power gone ? Can citizens be offered better maps of the corporate governance network, the financial system or the international trade network ?  Aren’t such maps necessary to embed in the democratic process the redrawing of boundaries between the public and the private spheres, the public and the private sectors, communities and cities, membership and governance ?




Two series of questions



Global Markets I : Thursday, 8th November 2012, 15.15 -16.45


- What is unique about our system of globally interconnected markets that  materializes itself in this massive flow of data ? i.e “Big data” is the symptom of what ?

- How can this data be used to better understand the system which generates it?

- How can models parse and/or explain this  “big data” ?

- What is specific to models of the global economic system ?

- For example, does increasing connectivity lead to increasing fragility, what transpires in models as volatile or even chaotic behavior ?



Global Markets II: Friday, 9th November 2012, 10.30 -12.30:


-How can  models using « big data » be more useful than existing ones for policy purposes ?

- What kind of models can be used for « emergency » economic and financial  management ?  By who and how ?

-What kind of models can be used for long-term issues such as strategic planning  or scenario generation ?  By who and how ?

- What kind of models do we need to better manage the transition to a green economy ?

-How can models improve public understanding of the dynamics of global systems ?

What would  be the impact of on governance ?

Green Growth in Global Systems Science

ECB President Mario Draghi, on September 6th, 2012, stated that

the assessment of the Governing Council is that we are in a situation now where you have large parts of the euro area in what we call a “bad equilibrium“, namely an equilibrium where you may have self-fulfilling expectations that feed upon themselves and generate very adverse scenarios. [see here]

At the same time, the current fossil-fuel-based economy, with its CO2 emissions, constitutes a “bad equilibrium” for the climate system. Green growth as a strategy to move from a bad equilibrium to a good one in these two dimensions seems a worthy research topic for global systems science. The Eurozone crisis and sustainability are largely discussed in disjoint debates. Global systems science could combine these two current challenges in order to identify cross-benefits between policies targeted at either one of them.

Germany’s “Energiewende” – a transformation towards an energy-efficient and green economy – could be an element of a strategy to move to a better equilibrium. Unfortunately, the recent public debate in Germany seems to be missing this point. Started off by the announcement that electricity prices will rise, due to a rising feed-in-tariff levy for renewable energy, the debate centers around these costs, and for the most part overlooks benefits that a consequently pursued green growth strategy would entail.

German Green Growth Model

We – the Lagom research group at the Global Climate Forum – are working on a model to study green growth opportunities, with a focus on Germany. The model shall be made available in a modular open-source framework, so that it can be combined with existing models providing more detail on particular sectors. By explicitly representing the possibility of multiple equilibria and corresponding growth paths for the economy in general, and the strongest European economy in particular, our research contributes important building blocks to the emerging Global Systems Science.

More detailed information on the project can be found here. The model development is based on a manifold dialogue with potential model users, experts of existing models, new economic thinkers and the general public. To extend this dialogue into the virtual world, we kindly invite comments, as well as a broader discussion of the arguments merely sketched above, on this blog.


Shaping Globalization

The global financial crisis has made one thing clear: we understand global systems much less than we thought, and if we are to meet the challenges of globalization that will define the 21st century we will need a lot of learning.

The EU has set up an open network of researchers under the title “Global Systems Dynamics and Policy” to foster such learning. Out of this effort the idea of Global Systems Science – GSS for short – has emerged. This blog – currently under construction – shall provide a platform for debate about how a research program for GSS might look like, and how it might be implemented.