Collaborative е-Rulemaking, Democratic Bots, and the Future of Digital Democracy

Abstract

This article focuses on "deliberative e-rulemaking": digital consultation processes that seek to facilitate public deliberation over policy or regulatory proposals [1, 2]. The main challenge of е-rulemaking platforms is to support an "intelligent" deliberative process that enables decision makers to identify a wide range of options, weigh the relevant considerations, and develop epistemically responsible solutions. This article discusses and critiques two approaches to this challenge: The Cornell RegulationRoom project and model of computationally assisted regulatory participation by Livermore et al. It then proceeds to explore two alternative approaches to e-rulemaking: One is based on the implementation of collaborative, wiki-styled tools. This article discusses the findings of an experiment, which was conducted at Bar-Ilan University and explored various aspects of a wiki-based collaborative е-rulemaking system. The second approach follows a more futuristic approach, focusing on the potential development of autonomous, artificial democratic agents. This article critically discusses this alternative, also in view of the recent debate regarding the idea of "augmented democracy." CCS Concepts: • Social and professional topics → Governmental regulations; • Applied computing → Egovernment;

Environmental Rule of Law: Tracking Progress and Charting Future Directions

“…Using technology as a tool for civic engagement is not new. Before the pandemic, the use of technology in the democratic processes of environmental decision-making was expanding, with growth at the international, national and local levels (Pérez 2020). A shift was already underway from physical public participation platforms to virtual spaces where physical participation tools were remodelled and adapted, and innovative facilitation techniques were employed (Elstub and Escobar Rodríguez 2019).…”

“…Inequalities in internet access across countries and stakeholders can lead to exclusion, as discussed in section 3.3.2.4. As more governments adopt this e-democracy model, these issues are becoming more evident (Pérez 2020).…”

Improving human collective decision-making through animal and artificial intelligence

“…A third approach that requires a democratic debate makes it technically possible for citizens to be represented by avatars reflecting the preferences of each voter rather than by politicians (Perez 2020). Technically, it will soon be possible to create intelligent e-democracy bots that can infer the political preferences of their associated human voter.…”

“…Technically, it will soon be possible to create intelligent e-democracy bots that can infer the political preferences of their associated human voter. Such bots could then be allowed to participate in voting processes on the voter's behalf (Perez 2020). For example, these bots could use Natural Language Processing (NLP) to copy the opinion expressed by the politician deemed closest to the voter's position.…”

Emerging Complexity in Distributed Intelligent Systems

“…Considering artificial intelligence (AI) agents within the DAI approach, an emergent collaboration and self-organized interaction often appear, pushing a swarm intelligence [ 6 ] and related ideas to an entirely new level. Emerging collaboration in bots is observed and even hired in different areas (Wikipedia editing [ 7 ], e-Government [ 8 ], etc.). Together with a deeper understanding of human–bot interaction [ 9 , 10 ], it leads to the idea that systems with AI agents and humans (expert, users, operators, etc.)…”