Crowdsourcing Mechanism Design

Yuko Sakurai, Masafumi Matsuda, Masato Shinoda, Satoshi Oyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Crowdsourcing is becoming increasingly popular in various tasks. Although the cost incurred by workers in crowdsourcing is lower than that by experts, the possibility of errors in the former generally exceeds that of the latter. One of the important approaches to quality control of crowdsourcing is based on mechanism design, which has been used to design a game’s rules/protocols so that agents have incentives to truthfully declare their preferences, and designers can select socially advantageous outcomes. Thus far, mechanism design has been conducted by professional economists or computer scientists. However, it is difficult to recruit professional mechanism designers, and developed mechanisms tend to be difficult for people to understand. Crowdsourcing requesters have to determine how to assign tasks to workers and how to reward them. Therefore, a requester can be considered to be an “amateur mechanism designer”. This paper introduces the “wisdom of the crowd” approach to mechanism design, i.e., using crowdsourcing to explore the large design space of incentive mechanisms. We conducted experiments to show that crowd mechanism designers can develop sufficiently diverse candidates for incentive mechanisms and they can choose appropriate mechanisms given a set of candidate mechanisms. We also studied how the designers’ theoretical, economic, and social tendencies, as well as their views on the world, justifiably affect the mechanisms they propose.

Original languageEnglish
Title of host publicationPRIMA 2017
Subtitle of host publicationPrinciples and Practice of Multi-Agent Systems - 20th International Conference, Proceedings
EditorsAna Bazzan, Serena Villata, Bo An, Joao Leite, Leendert van der Torre
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783319691305
Publication statusPublished - 2017
Event20th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2017 - Nice, France
Duration: Oct 30 2017Nov 3 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10621 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other20th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2017

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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