The group included scientists and (at least) two people with experience of applying scientific methods in a policy context, one from a company with 300,000 employees worldwide.

The context for the discussion was the paper on GSS by Ralph Dum (available on this site).

There was consensus that Global System Science is policy oriented.

The term ‘global’ is interpreted as meaning the whole system and can apply at different levels including the city level, national level and international level worldwide. Global system have entangled subsystems that cannot be analysed in isolation, e.g. water, waste, power, transport, housing, crime, employment, climate, etc. Geography and history (path dependence) are usually important. Global systems have many levels.

There was (implicit) consesus that GSS involves systems of systems and networks of networks.

Some systems have to be modelled bottom-up from individual agents.

Although we believe GSS must involve policy, scientists are not good at interfacing to policy makers. The example was given of working with the mayor of a large city. These are smart people who handle complexity all the time. The example included talking to the mayor to understand how they see their problems, and pointing out that the issues are coupled and may be best handled from a systems perspective.

Global systems science can be defined around POLICY INFORMATICS, i.e. building ICT systems to address particular policy issues. The example was given of the $180 million tem year research programme at Los Alamos that started with the US Federal Clean Air Act which could not be implemented because no-one understood how road traffic caused polutants (it can be noted that this generated new science).

There was a discussion of computability.

There was (implicit) consensus that GSS involves Big Data.

Global System Science can be viewed in terms of coordination failure. This can include faliyre cascades. This was considered to be a fruitful direction.

Much more was discussed. The following points were made in conclusion:

* we need to make a bridge between scientists and policy makers
scientists need to usnderstand the language and methods of policy makers
scientists need to be better communicators (some are better at this than others)

* it is useful to consider coordination faliures and cascades of failure
we need a list of exemplar Global Systems
this can help to make the bridge

* we are close to having useful modelling of heterogeneous agents on (changing) (multilevel) networks (of networks)

+ there is the issue of computatiblity (related to topology, local v global) and new ideas in computation.

sorry for leaving a lot out, more to come …

In the meantime we all read Ralph Dum’s paper for the next session.