Policy making improvement through social learning

Abstract

The world for which policies have to be developed is becoming increasingly complex, uncertain and unpredictable. Citizens are better informed, have rising expectations and are making growing demands for services tailored to their individual needs. The traditional policy-making process - where identification of problems and solutions given are defined by a small group of politicians and experts - is characterized by several inefficiencies: risk of false identification of problems, misled setting of goals, wasted resources, unsatisfactory evaluation and, above all, inefficiently addressed societal problems. The main goal of paper is to address the above mentioned challenges through the exploitation of social learning and supporting ICT techniques for a more efficient and open policy making process. These will enable better motivation to participate by taking each opinion into account for the final solution. The paper discusses our Centralab ICT solution as a supporting environment for policy modeling. The aim of our solution is not to change policy-making processes but rather to support them with innovative ICT tools to reach the overall goal when policy-making results in better quality of democracy and improved civic capacity. © 2013 Springer-Verlag Berlin Heidelberg.