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Creating Experts From the Crowd: Techniques for Finding Workers for Difficult Tasks
Citation key 1461Gottlieb2014
Author Luke Gottlieb and Gerald Friedland and Jaeyoung Choi and Pascal Kelm and Thomas Sikora
Pages 2075–2079
Year 2014
DOI 10.1109/TMM.2014.2347268
Journal IEEE Transactions on Multimedia
Volume 16
Number 7
Month nov
Abstract Crowdsourcing is currently used for a range of applications, either by exploiting unsolicited user-generated content, such as spontaneously annotated images, or by utilizing explicit crowdsourcing platforms such as Amazon Mechanical Turk to mass-outsource artificial-intelligence-type jobs. However, crowdsourcing is most often seen as the best option for tasks that do not require more of people than their uneducated intuition as a human being. This article describes our methods for identifying workers for crowdsourced tasks that are difficult for both machines and humans. It discusses the challenges we encountered in qualifying annotators and the steps we took to select the individuals most likely to do well at these tasks.
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