Fairness and transparency in crowdsourcing

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

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

4 Citations (Scopus)

Abstract

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
PublisherOpenProceedings.org
Pages466-469
Number of pages4
Volume2017-March
ISBN (Electronic)9783893180738
DOIs
Publication statusPublished - 2017 Jan 1
Event20th International Conference on Extending Database Technology, EDBT 2017 - Venice, Italy
Duration: 2017 Mar 212017 Mar 24

Other

Other20th International Conference on Extending Database Technology, EDBT 2017
CountryItaly
CityVenice
Period17/3/2117/3/24

Fingerprint

Transparency
Specifications
Compensation and Redress

Keywords

  • Crowdsourcing
  • Declarative transparency
  • Fairness

ASJC Scopus subject areas

  • Information Systems
  • Software
  • Computer Science Applications

Cite this

Borromeo, R. M., Laurent, T., Toyama, M., & Amer-Yahia, S. (2017). Fairness and transparency in crowdsourcing. In Advances in Database Technology - EDBT 2017: 20th International Conference on Extending Database Technology, Proceedings (Vol. 2017-March, pp. 466-469). OpenProceedings.org. https://doi.org/10.5441/002/edbt.2017.46

Fairness and transparency in crowdsourcing. / Borromeo, Ria Mae; Laurent, Thomas; Toyama, Motomichi; Amer-Yahia, Sihem.

Advances in Database Technology - EDBT 2017: 20th International Conference on Extending Database Technology, Proceedings. Vol. 2017-March OpenProceedings.org, 2017. p. 466-469.

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

Borromeo, RM, Laurent, T, Toyama, M & Amer-Yahia, S 2017, Fairness and transparency in crowdsourcing. in Advances in Database Technology - EDBT 2017: 20th International Conference on Extending Database Technology, Proceedings. vol. 2017-March, OpenProceedings.org, pp. 466-469, 20th International Conference on Extending Database Technology, EDBT 2017, Venice, Italy, 17/3/21. https://doi.org/10.5441/002/edbt.2017.46
Borromeo RM, Laurent T, Toyama M, Amer-Yahia S. Fairness and transparency in crowdsourcing. In Advances in Database Technology - EDBT 2017: 20th International Conference on Extending Database Technology, Proceedings. Vol. 2017-March. OpenProceedings.org. 2017. p. 466-469 https://doi.org/10.5441/002/edbt.2017.46
Borromeo, Ria Mae ; Laurent, Thomas ; Toyama, Motomichi ; Amer-Yahia, Sihem. / Fairness and transparency in crowdsourcing. Advances in Database Technology - EDBT 2017: 20th International Conference on Extending Database Technology, Proceedings. Vol. 2017-March OpenProceedings.org, 2017. pp. 466-469
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