Monthly Archives: July 2009
Over the last couple of years, the social sciences have been increasingly interested in using computer-based tools to analyze the complexity of the social ant farm that is the Web. Issuecrawler was one of the first of such tools and today researchers are indeed using very sophisticated pieces of software to “see” the Web. Sciences-Po, one of these rather strange french institutions that were founded to educate the elite but which now have to increasingly justify their existence by producing research, has recently hired Bruno Latour to head their new médialab, which will most probably head into that very direction. Given Latour’s background (and the fact that Paul Girard, a very competent former colleague at my lab, heads the R&D departement), this should be really very interesting. I do hope that there will be occasion to tackle the most compelling methodological question when in comes to the application of computers (or mathematics in general) to analyzing human life, which is beautifully framed in a rather reluctant statement from 1889 by Karl Pearson, a major figure in the history of statistics:
“Personally I ought to say that there is, in my own opinion, considerable danger in applying the methods of exact science to problems in descriptive science, whether they be problems of heredity or of political economy; the grace and logical accuracy of the mathematical processes are apt to so fascinate the descriptive scientist that he seeks for sociological hypotheses which fit his mathematical reasoning and this without first ascertaining whether the basis of his hypotheses is as broad as that human life to which the theory is to be applied.” cit. in. Stigler, Stephen M.: The History of Statistics. Harvard University Press, 1990 p. 304
This spring worked on an R&D project that was really quite interesting but – as it happens with projects – took up nearly all of my spare time. La montre verte is based on the idea that pollution measurement can be brought down to street level if sensors can be made small enough to be carried around by citizens. Together with a series of partners from the private sector, the CiTu group of my laboratory came up with the idea to put an ozone sensor and a microphone (to measure noise levels) into a watch. That way, the device is not very intrusive and still in direct contact with the surrounding air. We built about 15 prototypes, based on the fact that currently, Paris’ air quality is measured by only a handful of (really high quality) sensors and even the low resolution devices we have in our watches should therefore be able to complement that data with a geographically more fine grained analysis of noise and pollution levels. The watch produces a georeferenced measurement (a GPS is built into the watch) every second and transmits the data via Bluetooth to a Java application on a portable phone, which then sends every data packet via GPRS to a database server.
My job in the project was to build a Web application that allows people to interact with and make sense of the data produced by the watches. Despite the help from several brilliant students from our professional Masters program, this proved to be a daunting task and I spent *at lot* of time programming. The result is quite OK I believe; the application allows users to explore the data (which is organized in localized “experiments”) in different ways, either in real-time or afterward. With a little more time (we had only about three month for the whole project and we got the hardware only days before the first public showcase) we could have done more but I’m still quite content with the result. Especially the heatmap (see image) algorithm was fun to program, I’ve never done a lot of visual stuff so this was new territory and a steep learning curve.
Unfortunately, the strong emphasis on the technological side and the various problems we had (the agile methods one needs for experimental projects are still not understood by many companies) cut down the time for reflection to a minimum and did not allow us to come up with a deeper analysis of the social and political dimensions of what could be called “distributed urban intelligence”. The whole project is embedded in a somewhat naive rhetoric of citizen participation and the idea that technological innovation can solve social problems, in this case matters of urban planning and local governance. A lesson I have learned from this is that the current emphasis in funding on short-term projects that bring together universities and the industry makes it very difficult to carve out an actual space for scientific practice between all the deadlines and the heavy technical demands. And by scientific practice, I mean a *critical* practice that does not only try to base specifications and prototyping on “scientifically valid” approaches to building tools and objects but which includes a reflection on social utility that takes a wider view than just immediate usefulness. In the context of this project, this would have implied a close look at how urban development is currently configured in respect to environmental concerns in order to identify structures of governance and chains of decision-making. This way, the whole project could have targeted issues more clearly and consciously, fine-tuning both the tools and the accompanying discourse to the social dimension it aimed at.
I think my point is that we (at least I) have to learn how to better include a humanities-based research agenda into very high-tech projects. We have known for a long time now that every technical project is in fact a socio-technical enterprise but research funding and the project proposals that it generates are still pretending that the “socio-” part is some fluffy coating that decorates the manly material core where cogs and wire produce tangible effects. As I programmer I know how difficult and time-consuming technical work can be but if there is to be a conscious socio-technical perspective in R&D we have to accept that the fluffy stuff takes even more time – if it is done right. And to do it right means not only reading every book and paper relevant to a subject matter but to take the time to reflect on methodology, to evaluate every step critically, to go back to the drawing board, and to include and to produce theory every step of the way. There is a cost to the scientific method and if that cost is not figured in, the result may still be useful, interesting, thought-provoking, etc. but it will not be truly scientific. I believe that we should defend these costs and show why they are necessary; if we cannot do so, we risk confining the humanities to liberal armchair commentary and the social sciences to ex-post usage analysis.