Growing mistrust of governments and experts has revived the ancient Greek method of empowering the public to participate in politics, and citizen assemblies are increasingly common . In France, for example, citizens’ assemblies have been convened to deliberate responses to climate change .
But selecting the members of these organs is a complicated task. Ideally, citizens’ assemblies should be representative and chosen at random . Balancing these two requirements is a major challenge, as volunteers tend not to be representative of the entire population.
In an age when respect for professional politicians is declining, algorithms could improve an alternative form of representative democracy .
A team of computer scientists from Harvard and Carnegie Mellon universities has come up with a potential solution: selection algorithms , according to a study published in Nature .
The algorithm first builds a set of quota-dependent panels. These are developed by iteratively building an “optimal portfolio” of panels and calculating the fairest distribution of participants. A single panel is then randomly drawn from the distribution.
The open source algorithm has already been used to select more than 40 citizen assemblies from around the world. In Michigan, the system was used to select a panel of 30 residents to make recommendations on COVID-19 .
The researchers will now explore new ways in which computing can contribute to democratic practices.