There's a set of old ideas that are getting some recent attention.

I think it’s possible to have a dynamic concept of sustainability … but then it becomes resilient sustainability. Or at least that’s what I teach my MBA students, that true sustainability is in fact resilience.

One crucial aspect of resilience in a complex “system of systems”, whether it’s a network of computer systems or a network of individual economic agents interacting in a network of markets (or the intersection of the two!), is the extent to which the different parts of the systems are “coupled”. That’s what I’ve been mulling over for the past week — loosely-coupled systems. Loose coupling is a term of art in computer systems. Interestingly, its Wikipedia entry caught my eye for the precise reason I wanted to incorporate it into this post:

Loose coupling describes a resilient relationship between two or more systems or organizations with some kind of exchange relationship. Each end of the transaction makes its requirements explicit and makes few assumptions about the other end.

This definition highlights the aspects that are important, especially from a smart grid architecture perspective and an institutional design perspective: different systems or organizations with some kind of exchange relationship. Loose coupling means that entities that are engaged in exchange have to understand and exchange certain kinds of information to make those exchanges happen, but these requirements are explicit, and they are not exhaustive. . .

Loose coupling is like having shock absorbers at the interfaces between different entities and different systems in a complex “system of systems”. Loose coupling can help prevent the negative consequences of unexpected actions from propagating through the network, and that’s how it contributes to resilience.

These are very, very old ideas for those with a background in agriculture or information systems architecture (or both). When such ideas are well understood and internalized the world looks a bit different. You begin to notice well designed systems and institutions in other fields of human and natural activity, and gain a sort of predictive power. Systems that are brittle look dangerous, no matter how beautiful and orderly they seem to authoritarians. You can safely short sell them since they will fail, so long as you can afford to ride out any temporary up moves on the way to failure.

Briefly, an example of this from current events is the use of David Li's Gaussian copula function which coupled individual probabilities of failure to come up with a single, simple estimate of risk. It's efficient as long as the estimate is good but when it is in error the whole system crashes. Going back a little further to the collapse of LTCM a decade earlier gives us another example.

If a random bolt of lightning hits you when you're standing in the middle of the field, that feels like a random event. But if your business is to stand in random fields during lightning storms, then you should anticipate, perhaps a little more robustly, the risks you're taking on.

Much of what I've written here over the years deals with aspects of this issue and applies it to various disciplines. The arguments for diversity, decentralization, redundancy, fall back positions, error handling, missing interrupt handling, expectation of the unexpected, deep ignorance, leverage, emergence and complexity aren't just the fussy fears of a timid personality, they are realistic engagement with the nature of systems of systems. It applies to sensible agronomic practices that avoid monoculture and rent seeking as much as to the old net-head/bell-head debates about the inherent burstiness of communication networks. Any system designed to optimize part of a problem will fail at some point, and the net benefit over time will be less than for better designed systems that anticipated, though couldn't precisely predict, failure.

If you have read the articles linked above, and read the articles linked in them, you might find this old post useful. Or this one.