Crowdsourcing, or the act of outsourcing a task to the crowd, has the potential to revolutionize information collection and processing systems by enabling in-depth, large-scale, and cost-effective information gathering, more accurate techniques for information extraction from data. Crowdsourced data processing is effective when humans are better than existing automated computer algorithms, for example labeling images, transcribing speech, annotating text, transcribing scanned documents, and so on. Crowdsourcing also provides a powerful mechanism for creating data about the physical world, particularly through the use of mobile phones and their rich set of on-board sensors (GPS, audio, video, etc). These sensors can be utilized to provide continuous and unprecedented visibility into the state of the world across many scales.

This course is an exploration of the opportunities and challenges of crowdsourcing, and will discuss a variety of perspectives on the topic including applications, incentives, data quality assurance, privacy, general design principles, incorporation of ML/AI techniques, modeling, integration with social networks and cloud computing, etc. Students from diverse research backgrounds/interests are encouraged to attend for more productive discussion.

The course will primarily consist of reading, presenting, and discussing papers. In addition, students taking the class for 3 credits will be expected to define and execute a semester-long research project that relates to crowdsourcing, preferably using either the mCrowd platform provided by us for iPhone/Android phones or the Amazon Mechanical Turk.

Hours:
Mondays - 3:30pm - 5:30pm
Rm 142, CS Building

Instructor
Deepak Ganesan
250 CS Department
Email: dganesan AT cs DOT umass DOT edu
Course Mailing List: AT cs.umass.edu