ENCODE workshop over online deliberatie en massaparticipatie

Workshop Beschrijving 

In de deliberatieve democratie komt een centrale uitdaging voort uit het conflict tussen twee essentiële voorwaarden voor democratische legitimiteit: deliberatie aan de ene kant en massaparticipatie aan de andere kant. Volgens de deliberatieve democratische theorie zijn collectieve beslissingen immers legitiem wanneer ze het resultaat zijn van deliberatie onder al diegenen die door de beslissing worden beïnvloed. Wanneer de beslissing grote groepen mensen aangaat, is massale deelname noodzakelijk. Tegelijkertijd wordt gesteld dat goede deliberatie het beste werkt in kleine groepen.

Kan online participatie aan deliberatie dit probleem verhelpen? Zo ja, hoe ontwerpen we deliberatie online? Deze workshop wil inzicht geven in de verschillende uitdagingen en vragen die zich voordoen bij het ontwerpen van online deliberatie en massaparticipatie. We willen het onderwerp belichten vanuit filosofische, computationele en praktische invalshoeken.

De workshop wordt ondersteund door het NWO Vidi ENCODE project (Explicating the Norms of Collective Deliberation), gehost aan de Erasmus Universiteit Rotterdam, en wordt geleid door universitair hoofddocent Frederik Van De Putte.

Sprekers

De workshop bevat lezingen van:

Dannica Fleuss – e.a. Universiteit van Nairobi en Universiteit van Heidelberg
Dennis Frieß – Düsseldorfer Instituut voor Internet en Democratie (DIID)
Anna Michajlovskaja – Rijksuniversiteit Groningen
Michaël Grauwde – Technische Universiteit Delft
Feline Lindeboom – Rijksuniversiteit Groningen

Planning

• 11:30 - 11:45 - Coffee break
• 11:45 - 12:30 - Anna Mikhaylovskaya 
• 12:30 - 1:30 - Lunch break
• 1:30 - 2:30 - Dannica Fleuss
• 2:30 - 2:45 - Coffee break
• 2:45 - 3:30 - Feline Lindeboom
• 3:30 - 3:45 - Coffee break
• 3:45 - 4:30 - Michaël Grauwde
• 6:00 - Dinner

Abstracts (Engels)

Dennis Friess - Düsseldorfer Institut für Internet und Demokratie

Title & Abstract - TBA

Anna Mikhaylovskaya - University of Groningen

Title - Nurturing Virtues with Digital Democratic Innovations

Abstract - Digital democratic innovations (DDIs) have been widely discussed as a promising way of engaging citizens in political decision-making. Extensive research has focused on designing DDIs that are deliberative, inclusive, and representative. However, little attention has been paid to DDIs’ potential for nurturing individual democratic virtues. Our paper aims to address this gap. We argue that the cultivation of democratic virtues should play a more central role when it comes to digital citizen participation. Specifically, we explore how deliberative DDIs can help participants develop virtuous qualities. Beyond providing a more participatory decision-making mechanism, DDIs should be seen as an opportunity for individuals to cultivate virtues and become better citizens. We distinguish between epistemic and moral virtues, and explore how DDIs can nurture them in ways distinct from other forms of deliberative democratic innovations. To this end, we propose practical design features for DDI that could facilitate the cultivation of both epistemic and moral virtues.

Dannica Fleuss - University of Nairobi, Heidelberg University (a.o.)

Title & Abstract - TBA

Feline Lindeboom - University of Groningen

Title - A voice for minorities: diversity in approval based committee elections under incomplete or inaccurate information.

 Abstract - We study diversity in approval based committee elections with incomplete and/or inaccurate information. As standard in the literature on multi-winner voting, we define diversity according to the maximum coverage problem, which is known to be NP-complete, with a best attainable polynomial time approximation ratio of 1-1/e. In the incomplete information model, voters vote on only a small portion of the candidates. We suggest a greedy algorithm and a local search algorithm that query voters and use the query responses to approximate the total population's opinion. For both algorithms, we prove an upper bound on the number of queries required to get a close to 1-1/e -approximate solution with high probability. We also provide a lower bound for the query complexity of non-adaptive algorithms in this setting. In the inaccurate information setting, voters' answers are corrupted with a probability p in (0,1/2). We provide both an upper and a lower bound for the number of queries required to attain a 1-1/e approximate solution with high probability. Finally, using real data from Polis, we see that our algorithms perform better than the theory suggests, both with incomplete and inaccurate information.

Michaël Grauwde – Delft University of Technology

Title & Abstract - TBA