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Decision making at scale: Algorithms, Mechanisms, and Platforms
/ INRIA (Institut national de recherche en informatique et automatique), CNRS - Centre National de la Recherche Scientifique, UNS, Région PACA
/ 16-06-2016
/ Canal-u.fr
Goel Ashish
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Voir le résumé
YouTube
competes with Hollywood as an entertainment channel, and also
supplements Hollywood by acting as a distribution mechanism. Twitter has
a similar relationship to news media, and Coursera to Universities. But
there are no online alternatives for making democratic decisions at
large scale as a society. In this talk, we will describe two algorithmic
approaches towards large scale decision making that we are exploring.
a) Knapsack voting and participatory
budgeting: All budget problems are knapsack problems at their heart,
since the goal is to pack the largest amount of societal value into a
budget. This naturally leads to « knapsack voting » where each voter
solves a knapsack problem, or comparison-based voting where each voter
compares pairs of projects in terms of benefit-per-dollar. We analyze
natural aggregation algorithms for these mechanisms, and show that
knapsack voting is strategy-proof. We will also describe our experience
with helping implement participatory budgeting in close to two dozen
cities and municipalities, and briefly comment on issues of fairness.
b) Triadic consensus: Here, we divide
individuals into small groups (say groups of three) and ask them to come
to consensus; the results of the triadic deliberations in each round
form the input to the next round. We show that this method is efficient
and strategy-proof in fairly general settings, whereas no pair-wise
deliberation process can have the same properties.
This is joint work with Tanja Aitamurto, Brandon Fain, Anilesh
Krishnaswamy, David Lee, Kamesh Munagala, and Sukolsak Sakshuwong. Bio: Mot(s) clés libre(s) : problème knapsack, triadic consensus
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