Complexity and Systemic Risk: Hilary Term Seminar Series 2010 Oxford University

In order to understand social systems, it is essential to identify the circumstances under which individuals spontaneously start cooperating or developing shared behaviors, norms, and culture. In this connection, it is important to study the role of social mechanisms such as repeated interactions, group selection, network formation, costly punishment and group pressure, and how they allow us to transform social dilemmas into interactive situations that promote the social system. Furthermore, it is interesting to study the role that social inequality, the protection of private property, or the on-going globalization play for the resulting 'character' of a social system (cooperative or not). It is well-known that social cooperation can suddenly break down, giving rise to poverty or conflict. The decline of high cultures and the outbreak of civil wars or revolutions are well-known examples. The more surprising is that one can develop an integrated game-theoretical description of phenomena as different as the outbreak and breakdown of cooperation, the formation of norms or subcultures, and the occurrence of conflicts. Delivered by Professor Dirk Helbing, Professor of Sociology, in particular of Modeling and Simulation, Swiss Federal Institute of Technology Zurich, Switzerland.

We live in an increasingly interconnected world of 'techno-social' systems, where infrastructures composed of different technological layers are interoperating within the social component that drives their use and development. The multi-scale nature and complexity of these networks are crucial features in understanding and managing them. In the last decade advances in performance in computer technology, data acquisition and complex networks theory allow the generation of sophisticated simulations on supercomputer infrastructures to anticipate the spreading pattern of a pandemic, predict the traffic pattern of successful web sites or provides insight and recommendations in the case of natural or intentional disruptive events. In particular I will use the example of the current H1N1 pandemic and present computing tools with the ambition of anticipating trends, evaluating risks and eventually managing future public policies in real time. Delivered by Professor Alessandro Vespignani: Professor of Informatics, Indiana University Bloomington, USA. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

The oceans are a critical component of the climate system, storing roughly 1000 times as much heat, and 50 times as much carbon, as the atmosphere. In this talk, Professor David Marshall (21st Century Ocean Institute, University of Oxford) will discuss the challenges of predicting the evolution of a complex system that is grossly under-sampled and spans a bewildering range of scales in both space and time. These challenges will be illustrated through the important but over-sensationalised problem of how the Gulf Stream may change over the next century and impacts on European climate. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

Cities are getting more complex as their residents acquire more and more ways in which they can interact with one another. New technologies enable individuals to repackage their time and space in countless different combinations, and the flexibility afforded by such innovations makes possible many new ways in which individuals might react to this complexity. Behavioural change is considerably greater in the modern city than the medieval. Delivered by Professor Mike Batty: Director, Centre for Advanced Spatial Analysis, University College London. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

Growth, Innovation, and the Pace of Life from Cells and Ecosystems to Cities and Corporations; Are They Sustainable? Are cities and companies "just" very large organisms? They grow, metabolise, evolve and adapt; however, almost all cities survive, whereas all companies die. A quantitative, predictive, unifying framework for addressing such questions and understanding the generic structure, dynamics and life history of social and biological systems will be developed. It is based on general properties of the networks that sustain such complex systems and is inspired by the simplicity manifested by extraordinary "universal" scaling laws governing almost all characteristics of cities, companies and organisms. Examples discussed will include vascular systems, growth, cancer, aging and mortality, sleep, and evolutionary rates. When extended to cities and companies the theory shows why, in contrast to biology which is dominated by economies of scale, the overall pace of life, including rates of innovation, systematically accelerates. This has dramatic implications for growth, development and sustainability: innovation and wealth creation that fuel cities, corporations and economies, if left unchecked, lead to fatal singularities that potentially sow the seeds for their inevitable collapse. Delivered by Professor Geoffrey West: Distinguished Professor, Santa Fe Institute, New Mexico, USA. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

The recent banking crises have made it clear that increasingly complex strategies for managing risk in individual banks and investment funds (pension funds, etc) has not been matched by corresponding attention to overall systemic risks. Simple mathematical caricatures of 'banking ecosystems', which capture some of the essential dynamics and which have some parallels (along with significant differences) with earlier work on stability and complexity in ecological food webs, have interesting implications. In particular, strategies that tend to minimise risk for individual banks can - under certain circumstances - maximise the probability of systemic failure. This talk will first sketch these models and the ensuing conclusions. Delivered by Professor Lord Robert May of Oxford: Department of Zoology, University of Oxford. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/