@inproceedings{9f7f02d1b0c540939033c14ec6fc2887,
title = "Fairness and transparency in crowdsourcing",
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{\textquoteright} 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.",
keywords = "Crowdsourcing, Declarative transparency, Fairness",
author = "Borromeo, {Ria Mae} and Thomas Laurent and Motomichi Toyama and Sihem Amer-Yahia",
note = "Publisher Copyright: {\textcopyright} 2017, Copyright is with the authors.; 20th International Conference on Extending Database Technology, EDBT 2017 ; Conference date: 21-03-2017 Through 24-03-2017",
year = "2017",
doi = "10.5441/002/edbt.2017.46",
language = "English",
series = "Advances in Database Technology - EDBT",
publisher = "OpenProceedings.org",
pages = "466--469",
editor = "Bernhard Mitschang and Volker Markl and Sebastian Bress and Periklis Andritsos and Kai-Uwe Sattler and Salvatore Orlando",
booktitle = "Advances in Database Technology - EDBT 2017",
}