From Poisons to Antidotes: Algorithms as Democracy Boosters

33 Pages Posted: 17 Jan 2022

See all articles by Paolo Cavaliere

Paolo Cavaliere

University of Edinburgh - School of Law

Graziella Romeo

Bocconi University - Department of Law

Date Written: January 17, 2022

Abstract

Under what conditions can artificial intelligence contribute to political processes without undermining their legitimacy? Thanks to the ever-growing availability of data and the increasing power of decision-making algorithms, the future of political institutions is unlikely to be anything similar to what we have known throughout the last century, possibly with Parliaments deprived of their traditional authority and public decision-making processes largely unaccountable. This paper discusses and challenges these concerns by suggesting a theoretical framework under which algorithmic decision-making is compatible with democracy and, most relevantly, can offer a viable solution to counter the rise of populist rhetoric in the governance arena. Such a framework is based on three pillars: a. understanding the civic issues that are subjected to automated decision-making; b. controlling the issues that are assigned to AI; and c. evaluating and challenging the outputs of algorithmic decision-making.

Keywords: Democracy, Artificial Intelligence, Political rights, Decision-making

Suggested Citation

Cavaliere, Paolo and Romeo, Graziella, From Poisons to Antidotes: Algorithms as Democracy Boosters (January 17, 2022). Edinburgh School of Law Research Paper No. 2022/01, Available at SSRN: https://ssrn.com/abstract=4011291 or http://dx.doi.org/10.2139/ssrn.4011291

Paolo Cavaliere (Contact Author)

University of Edinburgh - School of Law ( email )

Old College
South Bridge
Edinburgh, EH8 9YL
United Kingdom

Graziella Romeo

Bocconi University - Department of Law ( email )

Via Roentgen, 1
Milan, Milan 20136
Italy

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
78
Abstract Views
8,573
Rank
553,078
PlumX Metrics