Tuesday, February 5, 2013

Antifragility and actor networks


Nassim Taleb’s recent book on Antifragility may have some implications for understanding actor networks. Taleb suggests a triad of system types: fragile, robust or resilient and antifragile. Fragile systems are ones that collapse under stressful events, robust or resilient systems remain relatively neutral in the face of stressful events, whilst antifragile systems positively respond, strengthening under stressful events. Within hazards analysis such a distinction might be very helpful in separating out communities that are vulnerable to hazards, those that hold their own and those that thrive in adversity.

 

Actor network theory, as outlined in an earlier blog, is a very useful method for mapping actants (human and non-human), their relationships and how these relationships operate in changing contexts.  Leaving aside the complicated and, sometimes competing, definitions and deep conceptual issues of this approach, there is much in the simple drawing of nodes and relations that could help in identifying the basis of antifragile behaviour as illustrated in the simple network below.

 

Actants in the network may try to align and co-ordinate the network of relations to produce the outcome that they desire. Supermarkets put pressure on farmers to produce vegetables for them, controlling the prices asked for vegetables, the transport available for vegetables and even finances by tying farmers into specific contracts. In other words, the supermarkets are key actants who have extended their co-ordination and alignment of the network in such a manner as to virtually control how it operates. But is this network fragile or not?

 

Questions of fragility and antifragility can be answered only when the network is stressed, only when an event causes disruption. The nature of such events will vary with the nature of the network; event characteristics that cause network disruption will always be context dependent. This means that it may not be possible beforehand to predict the fragility or otherwise of a network. It is only when under stress that parts of that network may buckle or may develop novel means of relieving or even using the stress to strengthen the network.  Likewise, events can be propagated through the network in a variety of ways, so although one seemingly similar event may point to a stress point or relationships in the network, once that stressed node is 'fixed', the next event may pick out and illuminate another, different stress point. 

 

Antifragile behaviour can result if an actant can exploit the stress within the network to ensure that their vision or goals for the network are increasingly likely after the disruptive event. This realignment or co-ordination of the network could result from taking over the function of other nodes or exploiting a relationship that enables an actant to more deeply embed the relationships it needs to achieve its ends as in the figure. A particular bad year for crops due to drought, for example, could provide an opportunity for farmers who invested in irrigation methods to dictate prices to major suppliers or to cheaply buy up the land of farmers who did not invest in irrigation. The relationships and nodes existed before the disruptive event, but the multiple impacts (or the multiple manners in which the event plays out in the network) open up a range of opportunities for antifragile actants. It is important to note that antifragility is only definable in relation to the disruptive event (or the multiple manifestations of that event). Similarly, antifragility is only noticed if actants exploit the disruption to improve or enhance their own position and power (expressed through alignment and co-ordination of the network).

 

It is through actions within the network of relationships that antifragility and fragility is expressed. It may be possible to begin to identify some general properties of actants and relationships that may enable antifragility, but it is only through the expression of these properties by actant’s actions during and after a disruptive event that such properties will be identified as important. Future blogs will begin to characterise such network based properties by exploring the response of actants to specific disruptive events.

 

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