Fairness and transparency in crowdsourcing

Ria Mae Borromeo, Thomas Laurent, Motomichi Toyama, Sihem Amer-Yahia

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

13 Citations (Scopus)


Despite the success of crowdsourcing, the question of ethics has not yet been addressed in its entirety. Existing efforts have studied fairness in worker compensation and in helping requesters detect malevolent workers. In this paper, we propose fairness axioms that generalize existing work and pave the way to studying fairness for task assignment, task completion, and worker compensation. Transparency on the other hand, has been addressed with the development of plug-ins and forums to track workers’ performance and rate requesters. Similarly to fairness, we define transparency axioms and advocate the need to address it in a holistic manner by providing declarative specifications. We also discuss how fairness and transparency could be enforced and evaluated in a crowdsourcing platform.

Original languageEnglish
Title of host publicationAdvances in Database Technology - EDBT 2017
Subtitle of host publication20th International Conference on Extending Database Technology, Proceedings
EditorsBernhard Mitschang, Volker Markl, Sebastian Bress, Periklis Andritsos, Kai-Uwe Sattler, Salvatore Orlando
Number of pages4
ISBN (Electronic)9783893180738
Publication statusPublished - 2017
Event20th International Conference on Extending Database Technology, EDBT 2017 - Venice, Italy
Duration: 2017 Mar 212017 Mar 24

Publication series

NameAdvances in Database Technology - EDBT
ISSN (Electronic)2367-2005


Other20th International Conference on Extending Database Technology, EDBT 2017


  • Crowdsourcing
  • Declarative transparency
  • Fairness

ASJC Scopus subject areas

  • Information Systems
  • Software
  • Computer Science Applications


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