Risk in a networked society
It’s hard to dispute the claim that society now is more inter-connected than it has ever been. Most of the time this hyperconnectivity is touted as a positive influence on society, but what are the risks involved?
That was the question asked by Dirk Helbeing in a recent paper on the risks of global networks, and how we can respond to those risks. Helbeing is most renowned for his social force model that analysed the way pedestrians move and self organise themselves.
The premise of the article is that the increased complexity of modern society caused by globalisation and technological advances can potentially make man-made systems unstable. These can “create uncontrollable situations, even when decision makers are well-skilled, have all data and technology at their disposal, and do their best”. He goes on to explain this through the lens of cascade effects.
“Our society is entering a new era—the era of a global information society, characterized by increasing interdependency, interconnectivity and complexity, and a life in which the real and digital world can no longer be separated. However, as interactions between components become ‘strong’, the behaviour of system components may seriously alter or impair the functionality or operation of other components. Typical properties of strongly coupled systems in the above-defined sense are: (1) Dynamical changes tend to be fast, potentially outstripping the rate at which one can learn about the characteristic system behaviour, or at which humans can react. (2) One event can trigger further events, thereby creating amplification and cascade effects, which implies a large vulnerability to perturbations, variations or random failures. Cascade effects come along with highly correlated transitions of many system components or variables from a stable to an unstable state, thereby driving the system out of equilibrium. (3) Extreme events tend to occur more often than expected for normally distributed event sizes”
Helberg goes on to explain that he believes the financial crash was an example of just such a cascade effect, whilst threats such as cyber warfare and pandemic diseases are other examples of potential man-made time bombs. To help manage this risk and uncertainty, he suggests re-designing the system.
“Managing complexity using self-organization. When systems reach a certain size or level of complexity, algorithmic constraints often prohibit efficient top-down management by real-time optimization. However, “guided self-organisation” is a promising alternative way of managing complex dynamical systems, in a decentralized, bottom-up way. The underlying idea is to use, rather than fight, the system-immanent tendency of complex systems to self-organize and thereby create a stable, ordered state. For this, it is important to have the right kinds of interactions, adaptive feedback mechanisms, and institutional settings. By establishing proper ‘rules of the game’, within which the system components can self-organize, including mechanisms ensuring rule compliance, top-down and bottom-up principles can be combined and inefficient micro-management can be avoided….
Coping with networked risks. To cope with hyper-risks, it is necessary to develop risk competence and to prepare and exercise contingency plans for all sorts of possible failure cascades. The aim is to attain a resilient (‘forgiving’) system design and operation…An additional principle of reducing hyper-risks is the limitation of system size, to establish upper bounds to the possible scale of disaster…. Last but not least, reducing connectivity may serve to decrease the coupling strength in the system…”
To provide for the necessary data that can be used by scientists to study global network risks, he along with his colleagues at the FutureICT project calls for the creation of an information infrastructure, or a “Planetary Nervous System”, which would be widely available.
“The data generated by the Planetary Nervous System could be used to feed a “Living Earth Simulator”, which would simulate simplified, but sufficiently realistic models of relevant aspects of our world. Similar to weather forecasts, an increasingly accurate picture of our world and its possible evolutions would be obtained over time as we learn to model anthropogenic systems and human responses to information. …
Finally, a “Global Participatory Platform”would make these new instruments accessible to everybody and create an open ‘information ecosystem’, which would include an interactive platform for crowd sourcing and cooperative applications.”