This project will investigate how technology-supported, large-scale crowd computing approaches can be used to strengthen the functions of democratic consultation and popular initiative procedures—arguably the most impactful participatory mechanisms of direct democracy, as they allow the population to not only strongly influence the outcome of the political process but also to set the agenda (in popular initiatives). Hence, this project will build novel hybrid human-machine systems that cultivate, coordinate, and support participants using coordination technology and artificial intelligence (AI) to support these functions in real world democratic settings. Given that these goals need to combine and advance our understanding regarding the political process, the legal framework, as well as modern technology, this project will combine scientific methods from political science, jurisprudence, AI, and computer-supported cooperative work. The insights of this project may prove to be crucial for a direct democracy like Switzerland, to foster democratic innovation and turn its citizens to even more active, AI-empowered participants in the democratic process—a goal which ultimately ensures democratic stability and our welfare.
In a typical election, citizens encounter a bewildering menu of parties vying for their vote. How do citizens cope with this abundance of choice and how does the coping mechanism affect the functioning of electoral democracy? These are the central questions of this book project. Building on consideration set models of choice, the book first presents a new micro-level theory of electoral democracy. It validates this with experimental and survey data. Next, it looks at the implication of the theory for party behavior and competition. Finally, it looks at system-level factors that affect choice behavior and answers the normative question of whether abundant choice can be too much of a good thing.