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Scientists Develop Selection Algorithm for Citizens Assembly

The ancient Athens democracy was peculiar than modern democracies. Rather than conducting elections, most of the offices—including governing councils, legislature, and magistrates—were occupied by citizen volunteers chosen by random lottery.

Citizens’ assemblies are bodies of randomly selected citizens to deliberate on important issues. A new algorithm ensures a fairer selection of participants for these assemblies. Image Credit: Pexels.

These citizen assemblies were responsible for drafting, debating, and passing laws. The assembly also made significant policy decisions and regulated military budgets.

The citizen’s assemblies are again gaining momentum now. In 2019 and 2020, such assemblies formed in the United Kingdom and France to lay out measures to tackle climate change. Even in Ireland, the citizen’s assembly has amended the Irish constitution by legalizing same-sex marriage and abortion.

An underlying difficulty in organizing these assemblies, both at present and at ancient times, is choosing the right person for the responsibility. The assembly requires being representative of the entire population. However, the selection must be random, ensuring a fair chance of opportunity for all volunteers.

For the objectives to be balanced, the ancient Athenians employed a rudimentary machine known as kleroterion, designed to randomly choose panels of volunteers from various tribes. A group of scientists has currently developed a 21st-century solution.

At present, a group of computer scientists from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and Carnegie Mellon University, in collaboration with a practitioner from the Sortition Foundation, has developed an assembly selection method that fulfills representation and fairness at the same time.

The study was published in the journal Nature.

Ideally, a citizens’ assembly acts as a microcosm of society. Whether this goal is realized in practice, however, depends on exactly how assembly members are chosen.

Ariel Procaccia, Study Co-Author and Gordon McKay Professor of Computer Science, Harvard John A. Paulson School of Engineering and Applied Sciences

First, we need to ask how do we even think about fairness in the context of panel selection, and then how do we formalize it in a way that means that everyone gets a fair chance,” stated Bailey Flanigan, study co-author and graduate student from Carnegie Mellon University.

The researchers assessed a normal two-stage assembly selection process. The first stage invited thousands of randomly selected people to participate. The final assembly has been chosen from the group of volunteers by making use of a selection algorithm. But the group of volunteers was regarded as unrepresentative of the population as certain groups, like those with high education, were more willing to represent.

Giving all volunteers exactly equal probabilities is generally impossible to do while also satisfying demographic quotas. Our selection algorithm finds a panel that satisfies quotas while giving potential participants as equal a chance as possible of being selected.

Paul Gölz, Study Co-Author and Graduate Student, Carnegie Mellon University

The system executes this by calculating a distribution over several panels, everything that fulfills the quota needs, and further randomly draws a panel from this distribution. Moreover, the distribution of panels is selected such that the lowest probability of any participant appearing on the panel is as high as mathematically possible.

Already, this open-source algorithm has been employed to choose over 40 citizen assemblies across the globe, by organizations in countries like Germany, Denmark, Belgium, United States, and the United Kingdom.

Procaccia, together with his study co-authors and GiliRusak of Stanford University, has designed a website known as Panelot.org, which makes their selection algorithm available at no cost. As a next step, the researchers will continue their collaboration with practitioners to understand their expressions regarding the working of these new selection algorithms and their potential.

We are excited to explore new ways in which math and computer science can contribute to the practice of democracy.

Ariel Procaccia, Study Co-Author and Gordon McKay Professor of Computer Science, Harvard John A. Paulson School of Engineering and Applied Sciences

This study was financially supported by the Office of Naval Research and by the National Science Foundation under grants CCF-1907820, CCF-1955785, CCF-2006953, CCF-2007080, and IIS-2024287.

Journal Reference:

Flanigan, B., et al. (2021) Fair algorithms for selecting citizens’ assemblies. Nature. doi.org/10.1038/s41586-021-03788-6.

Source: https://www.seas.harvard.edu/

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