AAAI

Association for the Advancement of Artificial Intelligence

Home > Proceedings / Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2

Glance Privacy: Obfuscating Personal Identity While Coding Behavioral Video

Authors

Mitchell Gordon,Walter Lasecki,Winnie Leung,Ellen Lim,Steven Dow,Jeffery Bigham

University of Rochester,Carnegie Mellon University,Carnegie Mellon University,Carnegie Mellon University,Carnegie Mellon University,Carnegie Mellon University


Published:

2014-11-05

Proceedings:

Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2

Volume

Issue:

Vol. 2 (2014): Second AAAI Conference on Human Computation and Crowdsourcing

Track:

Works in Progress

Downloads:

Download PDF

Abstract:

Behavioral researchers code video to extract systematic meaning from subtle human actions and emotions. While this has traditionally been done by analysts within a research group, recent methods have leveraged online crowds to massively parallelize this task and reduce the time required from days to seconds. However, using the crowd to code video increases the risk that private information will be disclosed because workers who have not been vetted will view the video data in order to code it. In this Work-in-Progress, we discuss techniques for maintaining privacy when using Glance to code video and present initial experimental evidence to support them.

DOI:

10.1609/hcomp.v2i1.13173


HCOMP

Vol. 2 (2014): Second AAAI Conference on Human Computation and Crowdsourcing


ISBN 978-1-57735-682-0