CrowdScale 2013
Crowdsourcing at a large scale raises a variety of open challenges:- How do we programmatically measure, incentivize and improve the quality of work across thousands of workers answering millions of questions daily?
- As the volume, diversity and complexity of crowdsourcing tasks increase, how do we scale the hiring, training and evaluation of workers?
- How do we design effective elastic marketplaces for more skilled work?
- How do we adapt models for long-term, sustained contributions rather than ephemeral participation of workers?
We believe tackling such problems will be key to taking crowdsourcing to the next level – from its uptake by early adopters today, to its future as how the world’s work gets done. To advance the research and practice in crowdsourcing at scale, our workshop invites position papers tackling such issues of scale. In addition, we are organizing a shared task challenge regarding how to best aggregate crowd labels on large crowdsourcing datasets released by Google and CrowdFlower. Organizers
Tatiana Josephy (@tatianajosephy), CrowdFlower Matthew Lease (@mattlease), University of Texas at Austin Praveen Paritosh (@heuristicity), Google
Advisory Committee
Omar Alonso, Microsoft Ed Chi, Google Lydia Chilton, University of Washington Matt Cooper, oDesk Peng Dai, Google Benjamin Goldenberg, Yelp David Huynh, Google Panos Ipeirotis, Google/NYU Chris Lintott, Zooniverse/GalaxyZooGreg Little, oDesk Stuart Lynn, Zooniverse/GalaxyZoo Stefano Mazzocchi, Google Rajesh Patel, Microsoft
Mike Shwe, GoogleRion Snow, Twitter Maria Stone, Microsoft Alexander Sorokin, CrowdFlower Jamie Taylor, Google Tamsyn Waterhouse, Google Patrick Philips, LinkedIn Sanga Reddy Peerreddy, SetuServ
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