consultation

How do you increase the quality of feedback without placing citizens on different-level playing fields from the outset—particularly where technology is concerned?

Ed: Given the “crisis in democratic accountability”, methods to increase citizen participation are in demand. To this end, your team developed some interactive crowdsourcing technologies to collect public opinion around an urban renovation project in Oulu, Finland. What form did the consultation take, and how did you assess its impact? Simo: Over the years we’ve deployed various types of interactive interfaces on a network of public displays. In this case it was basically a network of interactive screens deployed in downtown Oulu, next to where a renovation project was happening that we wanted to collect feedback about. We deployed an app on the screens, that allowed people to type feedback directly on the screens (on-screen soft keyboard), and submit feedback to city authorities via SMS, Twitter and email. We also had a smiley-based “rating” system there, which people could us to leave quick feedback about certain aspects of the renovation project. We ourselves could not, and did not even want to, assess the impact—that’s why we did this in partnership with the city authorities. Then, together with the city folks we could better evaluate if what we were doing had any real-world value whatsoever. And, as we discuss, in the end it did! Ed: How did you go about encouraging citizens to engage with touch screen technologies in a public space—particularly the non-digitally literate, or maybe people who are just a bit shy about participating? Simo: Actually, the whole point was that we did not deliberately encourage them by advertising the deployment or by “forcing” anyone to use it. Quite to the contrary: we wanted to see if people voluntarily used it, and the technologies that are an integral part of the city itself. This is kind of the future vision of urban computing, anyway. The screens had been there for years already, and what we wanted to see is if people find this type of service on their own when…

There has been a major shift in the policies of governments concerning participatory governance—that is, engaged, collaborative, and community-focused public policy.

Policy makers today must contend with two inescapable phenomena. On the one hand, there has been a major shift in the policies of governments concerning participatory governance—that is, engaged, collaborative, and community-focused public policy. At the same time, a significant proportion of government activities have now moved online, bringing about “a change to the whole information environment within which government operates” (Margetts 2009, 6). Indeed, the Internet has become the main medium of interaction between government and citizens, and numerous websites offer opportunities for online democratic participation. The Hansard Society, for instance, regularly runs e-consultations on behalf of UK parliamentary select committees. For examples, e-consultations have been run on the Climate Change Bill (2007), the Human Tissue and Embryo Bill (2007), and on domestic violence and forced marriage (2008). Councils and boroughs also regularly invite citizens to take part in online consultations on issues affecting their area. The London Borough of Hammersmith and Fulham, for example, recently asked its residents for thier views on Sex Entertainment Venues and Sex Establishment Licensing policy. However, citizen participation poses certain challenges for the design and analysis of public policy. In particular, governments and organisations must demonstrate that all opinions expressed through participatory exercises have been duly considered and carefully weighted before decisions are reached. One method for partly automating the interpretation of large quantities of online content typically produced by public consultations is text mining. Software products currently available range from those primarily used in qualitative research (integrating functions like tagging, indexing, and classification), to those integrating more quantitative and statistical tools, such as word frequency and cluster analysis (more information on text mining tools can be found at the National Centre for Text Mining). While these methods have certainly attracted criticism and skepticism in terms of the interpretability of the output, they offer four important advantages for the analyst: namely categorisation, data reduction, visualisation, and speed. 1. Categorisation. When analysing the results…