Clay, picking his way through the exchange of posts about the significance of wikipedia, suggests there are two perspectives on technological innovation. One group of commentators use ‘Radial’ maps when describing innovation, valuing vectoral shifts out from a central point; whilst others use ‘Cartesian’ maps that value the final destination. Put in other terms, radial people get excited about iterative progress, and cartesian people look for the endgame. He suggests that writers like himself and Cory Doctorow are ‘radial’, whilst Danah Boyd and myself are ‘cartesian’, and that explains our different takes on the potential and limits of folksonomies.
At the risk of sounding even more ‘cartesian’, this is a ridiculous over-simplification, and artificially polarises the debate we were having about the impact of folksonomies as an innovation. I’m surprised that Clay – who I’ve long admired for the elegance and sophistication of his writing – has proposed such a binary opposition. It misinterprets some of the questions Danah and I were asking, dismissing them as symptoms of our cartesian worldview and us as being out of step with ‘an era of radial triumphs’. He then extends the cartesian analogy to explain why only companies who have a monopoly – or think they do – engage in pure research, as cartesian approaches to innovation require more resources over longer periods of time.
As someone who is currently engaged in an review of the entire R&D function where I work, this presses a number of my buttons at the same time. The lapsed academic in me wants to dig into Clay’s binary opposition and tease out a more complex model of innovation, whilst my work brain wants to demonstrate that current innovation best practise is to invest in a broad range of innovation and R&D strategies, some ‘cartesian’ and some ‘radial’. The second part will have to wait until after I can talk more publicly about the strategies we’re devising, so first of all, lets look at some alternative theoretical models for technological innovation.
Until quite recently, histories of science and technology have been polarised along similar lines to Clay’s radial/cartesian analogy – science discovers and technology applies. But in the last 20-30 years, researchers have been looking at the sociology of science and technology, mapping the dynamics between the two communities and the effects these dynamics have on innovation. Any period of innovation you care to choose has scientists who ‘do’ technology, and technologists who ‘do’ science – but the missing chapters in our technological histories describe the social networks that acted as crucibles for these communities and their products.
Bijker, Hughes and Pinch’s excellent ‘The Social Construction of Technological Systems’ proposes a new model for appraising technological innovation based on mapping the different professional and amateur communities that shared innovation problems, and tracing how the interaction of these communities led to the solution we now recognise as the ‘innovation’. Using the invention of the bicycle as an example, they demonstrate how innovation develops in a series of saccadic moves, nudged this way and that by the specific needs of each community. In the early development phase of the bicycle, many opposing solutions were available, but our traditional quasi-linear history describes a line between the boneshaker, penny farthing and the bicyclette, with other ‘failed’ options described as dead ends off this path. [click here to see this illustrated in a pop-up window]
Bijker et al propose a model that asks ‘why did some variants die whilst others survived?’. Their model explores the different social groups who shared the ‘problem’ driving the innovation. In the case of the bicycle, this includes the male audience targetted by bicycle manufacturers at the time (“Bicycling is a healthy and manly pursuit with much to recommend it, and, unlike other foolish crazes, it has not died out”), but also women (“From the number of [Safety Bicycles] adapted for the use of ladies, it seems as if bicycling was becoming popular with the weaker sex, and we are not suprised at it”) and even anti-cycling protest groups (“…stones are thrown, sticks thrust into the wheels, or caps hurled into the machinery. All the above in certain districts are a common occurrence, and have happened to me, especially when passing through a village just after school is closed”) [all quotes from contemporary sources quoted in Bijker et al].
The ‘Social Construction of Technology’ approach describes each group’s specific problem and aligns them to variant innovations that existed at the time. This approach introduces other factors other than the purely technological into our understanding of innovation:
“This way of describing the developmental process brings out clearly all kinds of conflicts: conflicting technical requirements by different social groups; conflicting solutions to the same problem (for example, the safety low-wheelers and the safety ordinaires); and moral conflicts (for example, women wearing skirts or trousers on high-wheelers). Within this scheme, various solutions to these conflicts and problems are possible – not only technological ones but also judicial or even moral ones (for example, changing attitudes toward women wearing trousers).”
[Bijker et al; “Social Construction of Facts and Artifacts”]
This is a far more sophisticated approach to understanding the drivers for technological innovation – closer to the PEST/PESTLE analysis used in scenario planning than the technological deterministic rhetoric that tends to dominate contemporary debate. Instead of innovation being depicted as a single line, it is a complex network of innovations and communities [click here to see this illustrated in a pop-up window].
I would propose this model is closer to the ‘map’ that Danah and I are using to discuss wikipedia and folksonomies than Clay’s reduction of us to a ‘cartesian’ perspective. Bringing other potential actors or drivers to the debate is not symptomatic of a worldview that fetishises ‘end-goals’ at the expense of iterative progress, but instead looks to make the fascinatingly complex network of existing actors even richer and more diverse. If anything, this approach is anti-cartesian, as it seeks to create a plurality of possible end-states, without fetishising one at the cost of the others. It values the iterative achievements of innovation communities, but puts them in the context of other actors and communities that might currently be invisble to them.
Ironically, this approach is a better conceptual fit to the radical commons-based production models we’re debating than the techno-centric ‘radial’ models Clay describes. As massively social forms of production become more and more significant, we should by all means celebrate the technological glue that enables them, but we should also start to examine the social communities that are simultaneously their users, creators, adapters and abusers.