1. We need a crisper definition of what we mean by GSS. All new fields suffer from this problem, but a first step to establishing GSS as a valuable new approach to solving global problems is to be able to explain concisely and in plain language what it means and intends.
2. Phenomenology In my experience it is hard to get modelers out of their offices, but frankly we have little structured understanding of what goes on in cities and this is most likely going to require a small army of Jane Jacobs’. The goal of this work is to develop archetypes of patterns and principles that can be refined over time by validating them in Big Database. I do not believe in simply collecting Big Data and then hoping that the data mining tools will find these patterns for us without any guidance.
3. I found the debates about how GSS will sort out the massive problems of global financial, governance,, climate change, and a few other problems to be very inspirational. I am sure we would all love to see these problems solved. But I generally encourage learning to walk before engaging in hyper-marathons. These problems have been around a long time and many very bright people have worked hard to solve them. Why should anyone believe the GSS can succeed where they have failed? We need some proof points based on tackling smaller but still quite important problems. There are many of these.
4. I was surprised that no one spoke about supply chain networks or more generally the ecosystems that bind multiple players together into industrial systems. These systems are rather invisible but have direct impacts on our lives when things go wrong, e.g. the Tohoku EQ, Hurricane Sandy. These are also the cradles of industrial innovation as networks are disrupted by new members or new technologies.
2 thoughts on “Research priorities from the workshop”
Armin re issue 3: I think Stefano’s work is a perfect example of a “small” but nevertheless thrilling exercise that combines approaches from ICT, network theory, financial markets theory, and down-to-earth double entry accounting. Moreover, it substantially makes use of data out there. Yesterday, Stefano added a further dimension when he presented his idea to invite the crowd to contribute to identifying ownership links in the global company network.
I would suggest to build on Stefano’s work and make it one specific showcase, and nucleus, for our GSS adventure.
I very much agree with Colin’s points. The first one is dogging me daily as a sustainability scientist. Sustainability is as (relatively) new as GSS, and to define it is a nightmare because the domain comprises essentially all human action and mindset, and there is no more or less generally accepted approach or toolkit that one can refer to, so that all disciplines have their own definitions. But more importantly, the term refers to a future characteristic of the systems we study, and is therefore indeterminate. Hence the more recent move towards ‘resilience’ as something that refers to a present system state.
In emerging fields of study like sustainability and GSS, some of the ‘fuzziness’ of the definition is inevitable, as we collectively first explore ‘what might fit the concept’ and only when that question has to some extent been answered, we can begin to define ‘what does not belong in the category’ – and thus begin to create other categories.
For me, in the case of GSS, two very important strands of thinking are combined. First of all, cross-scalar thinking from the microscopic to the macroscopic, from molecules to the whole of the global earth system (and back). This attempts to bridge a frequent gap between natural science thinking (which in the case of the earth system scales down from the global scale) and social science thinking (which scales up from the local or regional). Second, it emphasizes the systematic use of systems thinking (and preferably complex systems thinking) that studies the interaction between components or sectors that are more generally studied by (sub) disciplines. It thus introduces for many topics or fields of study a trans-disciplinary toolkit.
Thirdly, I see in this effort also a move towards thinking about the future rather than the past – about emergence of phenomena rather than about their origins, thinking in terms of scenarios rather than explanations, in terms of uncertainties, risks and opportunities rather than certainties.
We must find ways to explain this effectively and point to some case studies where such a change in approach has made a difference … Suggestions welcome.
As to Colin’s second point, there is in our community a disjuncture between the people who claim that the biggest challenge is the unavailability of data and those who signal a lack of hypotheses as the major challenge. This holds the field back, unless we can overcome the gap, by encouraging both strands of work and attempting to link them. ‘Middle-range’ theory may be a useful concept in this context. Mutual respect for both activities is essential.
The third point is an important one and a weakness in our current state of mind.
Finally, as to the industrial systems, clearly we need to include those, as became clear the day after the workshop in the (initially difficult) discussion with the WBCSD representative on their ‘action plan’. Apart from the evident importance of these systems, it is also becoming clearer that the technological logic that underpins these industrial systems is neither a ‘pure’ environmental logic, nor a pure ‘social’ one. This ‘hybrid’ logic dominates real life, and is woefully underrepresented in our thinking.