Editorial: Living analysis

Development Policy07 Apr 2008Frans Bieckmann

We’ve heard a lot about ‘Web 2.0’ lately, and now we’re starting to hear about ‘Science 2.0’. But what does ‘2.0’ actually mean? To me, ‘2.0’ refers to any process that enables the transparent sharing of insights, ideas and arguments in order to achieve a more comprehensive understanding.

For example, with Web 2.0, computers are no longer isolated tools, but access points in a dynamic social and collaborative network. Just think of a music-sharing site such as, the photo-sharing site, the free user-written resource Wikipedia and so on. Web 2.0 does not refer to a new version of the web, but rather to new ways of using existing technology. As a result, the whole is more than the sum of its parts.

I think Science 2.0 can have an equally exciting impact on the scientific community. With more open collaboration among scientists, we can gain better insight into our world and develop more effective approaches to improving it. By sharing existing and developing ideas more openly, we can add to the value and potential of these ideas. Here again, the whole would be more than the sum of its parts. ‘Science 2.0’ refers to the linking up of thousands or even millions of computers around the world to enable researchers to share insights, data and sources. Science 2.0 can be compared with basket funding or multilateral development cooperation: together you can do more, specialize more efficiently, reduce overheads and leave less of a footprint.

This view of Science 2.0 fits with new trends in how knowledge is used and exchanged. Luc Soete, director of UNU-MERIT, Maastricht, was one of many speakers at the recent Knowledge on the Move conference in The Hague. He discussed how the private sector is moving away from traditional research and development, which emphasizes creating new knowledge, to an approach focusing on finding new, unique and context-specific combinations of existing knowledge.

I often think of one of the terms we use in describing The Broker: ‘evidence-based’. You would be able to make much better policies, and produce better journalism, if you had access to up-to-date, evidence-based analyses of ongoing issues. But, particularly in the social sciences, evidence is never ‘absolute’. The best you can hope for is a reasonable approximation of the truth by, for example, having a large group of experts weigh in on a subject or event to see where they agree.

Take a recent example from the news: the ‘sudden’ outbreak of violence in Kenya, which was long thought to be one of the most stable countries in Africa. Experts grumbled that the mass media’s analyses were far too simplistic, putting the trouble down to ‘tribal violence’. Here and there, such experts would respond in an interview or editorial, but the overall media narrative was that the violence came as a surprise. You can read dozens of individual scientific treatises about such incidents – if you make the effort to read the more expensive scientific journals – but they are mostly written from one writer’s singularly focused analysis, and researchers do not collaborate to reach new decisions. Or you can wait years to read anything at all about an incident, long after it is over. If there is such a thing as an academic debate, it certainly does not address current events.

With the current collaborative, ‘2.0’ trend, I wonder if it might be possible to put together a sort of ‘wiki’, a public forum of sorts where up-to-date scientific analyses on a specific topic or event, like the conflict in Kenya, can be shared and debated. I would call it ‘living analysis’, because it would evolve in response to shifting reality, new developments and combined insights.

Suppose you drafted a five- to ten-page analytical text on a specific issue. Then suppose you allowed a bunch of experts to respond to it, paragraph by paragraph, sentence by sentence or even term by term, each from his or her point of view and area of expertise. These areas of expertise could be geographical, thematic, historical, political or whatever. If the majority of participants agreed on a certain sentence, you would leave it in, with links to texts and publications that support it (as is now possible with The Broker articles on the website). If there were no consensus, you would be able to click on links to read two (or more) different opinions, each with scientific arguments to support it. Or there might be a link to other websites featuring academic discussions on the specific ideas. But the original text itself would not get any longer, and a sentence would only be changed if there were a certain percentage of participants in favour of doing so.

The question is of course whether scientists would take part in such a living analysis. Just as donor coordination in a development cooperation is a worthy aim that is often obstructed in practice by donors pursuing their own interests. Scientists tend to be primarily concerned with themselves and their careers, and they focus on getting as many articles published as possible in the most prestigious journals. But here and there one hears calls from the scientific community to broaden that traditional system of ranking.

These living analyses would also need a template, a method. That was in the back of my mind when I decided to include an article on complexity theory in this issue of The Broker. In it, Alan Fowler describes an alternative way of looking at development, a way of analyzing how societies and the world as a whole change in continuous and interrelated processes.

I realize that including an abstract article like this is a risky experiment. It leaves The Broker open to criticisms such as, ‘Okay, everything is related to everything else, what good is that to anyone?’ As yet, there are no concrete applications for complexity theory in development; the article is, in effect, an appeal to think about potential applications. Take, for example, the thriving business of evaluation, which increasingly gets bogged down in the impossible task of describing linear relations in development processes that are infinitely more complex than just input-output-outcome-impact.

Perhaps the complexity article will contribute to solving what appears to be an insoluble paradox: on the one hand, the world is becoming more complex – or, at least, complexity is becoming more apparent through ICT and globalization. On the other hand, trivialization and simplification have the upper hand in most media – and are also gaining ground in the development cooperation, as can be seen from the increasing popularity of ‘do-it-yourself’ aid. We therefore need to find ways of articulating complexity to the outside world in a comprehensible manner. Complexity theory can help us to do that. Perhaps living analysis could do the same?