Digital Innovation and Open Government: Tools for an Open World?

Panel Code
Open Panel

The climate of mistrust towards politics and the crisis of legitimacy of both the traditional actors of representation and the different forms of political participation are elements widely present in the public debate and in contemporary political science literature. However, in the last two decades there have been several experiments and innovations, both in the way in which public sector institutions relate to the private sector and to citizens in general, and (more rarely) show how the internal decision-making processes of public administration are designed and organized. If the vision of open government has given these experiments a conceptual propulsion, the many forms of digital innovation have in many cases provided tools and practical applications with increasing potential. From an initial phase of enthusiasm and techno-optimism we have gradually passed to a period of more mature and disenchanted awareness of the limits and risks of an innovation that is not adequately conceived in terms of democratic values and quality of procedures.
This panel is aimed at promoting a reflection on the relevance of concrete open government experiments and on technological innovations that allow the rethinking of government processes and the relationship between the public sector, private subjects and citizens. A focus of interest, in this regard, is represented by smart cities and artificial intelligence, the use of open data and big data in the various phases of the policy cycle, the crowd law processes, gamification, portals of transparency, etc. This panel encourages a critical discussion on the impact of these initiatives in terms of the quality of democracy, even in a comparative perspective. Particular emphasis will be given to contributions able to highlight the relationship between the theory of democratic innovation and concrete practices, the impact and limits of such experiences, through specific case studies or in a comparative framework.