Expanding our Participatory Democracy Toolkit using Algorithms, Social Choice, and Social Science

In most of the world’s democracies, policy decisions are primarily made by elected political officials. However,under mounting dissatisfaction with representative government due to issues ranging from social inequality to public distrust, a  new proposal is taking off: to augment representative democracy with mechanisms by which the public can directly participate in policymaking.  

The guiding application of this thesis will be one particular model of participation, deliberative minipublics (DMs), though we will argue that our contributions  may apply to many models of direct participation. In a DM, a panel of citizens is  selected by lottery from the population; then, this panel convenes around a particular  policy issue to study background information, deliberate amongst themselves, and  then weigh in on the issue. DMs have been gaining momentum over the past decade,  and they are now being used at national and supranational levels, and are even being  integrated into representative governments.  

Motivated by this application domain, we make the following main contributions: In Part I, we design algorithms for performing the random selection of DM participants, a process known as sortition. Our sortition algorithms permit users  to make optimal trade-offs between descriptive representation and other desirable  properties conferred by randomness, and we characterize these tradeoffs using game theory, optimization, and empirics. In Part II, we use a novel social choice theory framework to investigate a notion of representation that departs from descriptive  representation in a key way: it accounts for the political reality that people may  be affected to widely varying degrees by any given policy decision. In Part III,  we study an important hypothesized impact of deliberation: increasing the extent to  which participants consider how others in their society may be affected by different  policies. In Part IV, we highlight how the enclosed research illustrates new ways to  combine tools from political science and computer science.