Faire online Gruppenentscheidungen (FairOGD)

Faire online Gruppenentscheidungen (FairOGD)

Today, a large part of our social interactions take place online. Consequently, the decision making of groups of individuals is more and more mediated by online tools of various forms. This includes decisions made by online communities, for example voting on the rules of the community or deciding which opinions or content to promote, as well as decisions about real-life interactions that are made using online tools, from the scheduling of meetings to larger digital democracy initiatives. However, most group decisions online are made using simple, majoritarian decision mechanisms, which often lead to unfair outcomes which do not adequately represent the opinions of minorities.

Fortunately, recent advances in the field of computational social choice (COMSOC) can provide the tools for fair or proportional online group decision making. However, this literature has so far focused on frameworks that do not capture crucial properties of online group decision making. Additionally, there is a lack of high-quality tools that make it easy for online communities to adopt the sometimes complex voting mechanisms the COMSOC literature proposes for fair decision making.

This project aims to address both of these difficulties by developing fair decision mechanisms which are suitable for online group decision making by building on the novel proportional voting rules developed within the COMSOC community in the last few years. Based on this research, we will develop and disseminate high-quality, ready-to-use tools for fair online decision making.

Themengebiet

Artificial Intelligence
,
Demokratie | Transparenz
,
Social Media

Technologie

AI | KI

Uni | FH [Universität]

WU Wien

Gesamtklassifikation

Studie|Konzept

Projektergebnisse

Veröffentlichung CC-BY

The paper "An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation" by Lars Bengel, Giovanni Buraglio, Jan Maly and Kenneth Skiba has been accepted at AAAI 2025

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