In my early foray into computer graphics in the late 80s I came across Symbolics, a spinoff of MIT AI Lab doing (among other things) research in advanced visualization. I was dumbfounded by this video, premiered by Symbolics at SIGGRAPH 1987. How could they achieve their flock of birds  to move in such a natural-looking way? At the time it looked like sorcery: I was a humble economics student in a small town in Italy, with not a chance in hell to grasp the extension of the knowledge wielded by MIT computer whizs. So I put it away in a corner on my mind. Until, in 2009, I chanced on a 1992 book, Mitchell Waldrop’s Complexity, that actually knows the answer to my 22-year old question. Each bird or fish in the flock follows three simple rules of behaviour:

1. It tries to maintain a minimum distance from other objects in the environment, including other birds/fish (Symbolics’ Craig Reynolds called them “boids”).
2. It tries to match velocities with nearby birds/fish.
3. It tries to move toward the perceived center of mass of nearby birds/fish.

The natural-looking flocking behaviour is emergent. As far as the program is concerned, there is no entity called flock: it is just moving about individual boids. Simple rules for local interaction among them produce an elegant and effective collective behaviour.

Wait a minute. This is not so different from what is happening in Kublai. Example: we wanted the community to go and say hello to new members. Of course you cannot issue a decree that this is to happen. So what we did was this: Walter and I, who are friends and also particularly active community members, agreed that we would do it, created a Welcome Group and started doing just that. This produced some sort of flocking behaviour: our “net neighbours” (at least some of them) started imitating us, and joined the group. Soon they developed a more effective way to keep track of who was doing what (after some trial-and-error Pico proposed a widget which everyone was happy with), and their net neighbours started following their example… including the initiators!

Communities are, by definition, impossible to control: but they are certainly possible to influence. This is no rocket science: most of us have some experience of it. This flocking behaviour intuition, if confirmed by analysis, could lead to developing techniques for influencing (not sure “managing” is the appropriate word) social networks based on establishing “islands” of local interactions where certain rules apply, and watching them spread out through the network’s links. Of course where you start matters: it just so happens that Walter and I are by far the most eigenvector central people in Kublai, according to Ruggero.

I am wondering whether this mechanism could somehow help us understand why people seem “too eager” to collaborate in social networks, and why, conversely, oppurtunistic behaviour is a lot less widespread than one would be inclined to think (this remark run in several talks at Public Services 2.0). Cooperation as an emergent property of networks, as opposed to an intrinsic property of individuals?

Er… I’m an economist actually, madam. True though, my working tools have been kind of unusual over the latest years, since I started working on the creativity/innovation/development nexus: not only blogs and social networks, but also parties, barcamps and Second Life-Real Life mashups. Much if the stuff I do feels right, and a lot of it goes surprisingly well, but it is by no means easy being confident that I really am getting it right, and that I am not missing out important opportunities simply because I do not see them. The economics I studied at college does not help me in this; nor do the intellectual contributions picked up along the way, from game theory to new economic geography, from the regional analysis of innovation à la Saxenian to public choice theory, important as they are. And when you find itself spending taxpayer money to improve your Second Life avatar to generate credibility (ok, that was about five dollars, but it’s the concept that matters), well, then it’s time to update your theoretical framework.

I looked around for a few years and I think I have spotted a promising thread in complexity economics. It is the attempt to apply to the economic domain a conceptual framework that developed in completely different disciplines, from biology to meteorology, in which the classic approach based on reductionism and determinism was not yielding results. Though this approach can be traced back to – surprise surprise – Viennese school economists, Von Hayek in particular, the birthplace of the concept of complex system is generally thought to be the Santa Fe Institute. So I started to hang out with David A. Lane, who worked in Santa Fe and now teaches in Italy, and to exchange some thoughts with him. Lately we have been speaking a lot about Kublai, and two of his students are trying to conceptualize the Kublai social network as a complex system: the approach seems interesting, we’ll see what comes out of it.

Meanwhile I have started to read Complexity Perspectives on Innovation and Social Change, by David and others (forthcoming). Compared with his articles of the late 90s and early 2000s there is a noticeable development: the “complexity approach” of that time is turning into a full-fledged economic theory. And it accounts for something that IMHO badly needs accounting for: namely, that technical innovation does not exist. What does exist in innovation, that happens in the agents-artifacts-culture space, and that involves people, modes of interaction, new artifacts and the set of attributions concerning all of the above. Technology is a part of this, and it does not make sense analytical sense to separate it out from the whole.

For a plain, rank-and-file economist like myself, spoonfed on Keynes and Edgeworth, reading this stuff is like going on some kind of psychedelic trip. I read of “Darwinian accounts”, “funcional orthogonality”, “agent-artifact space”, “attributional shifts” and even “exaptive bootstrapping dynamics” – a locution which I have not even been able to translate into Italian – until my brain starts to smoke like on old, overheated engine. But it’s good, very good, and well worh the effort. And I can’t help thinking – with some kind of warped professional pride – that David teaches in a department of economics: there must be something right in a discipline that can question itself so deeply, and to keep on giving me, after twenty odd years, new stimuli.