Title: Socio-technical Challenges in Scientific and Medical Crowdsourcing
Speaker: Edith Law, Assistant Professor in Computer Science, University of Waterloo
Date: April 17, 2018
Room: Gates-Hillman Complex 6501
Science is increasingly data-intensive; yet, many research tasks involving the collection, annotation and analysis of data are too complex to be fully automated. The idea of research-oriented crowdsourcing is to engage people without formal academic training to contribute or process data towards answering questions. In this talk, I will discuss the variety of socio-technical challenges that arise when designing scientific and medical crowdsourcing systems, and demonstrate through examples various situations where conventional approaches to crowdsourcing fall short.
Dr. Edith Law is an assistant professor at the David R. Cheriton School of Computer Science at University of Waterloo, where she co-directs the Human Computer Interaction (HCI) Lab. Her research focuses on studying how humans can augment and make sense of intelligent systems, as well as developing new curiosity-based strategies for engaging users and encouraging long-term interactions between humans and machines. Previously, she was a postdoctoral fellow at the School of Engineering and Applied Sciences at Harvard University. She graduated from Carnegie Mellon University in 2012 with Ph.D. in Machine Learning, and holds a M.Sc. in Computer Science from McGill University, and B.Sc. in Computer Science from University of British Columbia. She co-authored the book “Human Computation” and helped create the first AAAI Conference on Human Computation and Crowdsourcing (HCOMP). Her work on games with a purpose, large-scale collaborative planning and curiosity as an incentive mechanism have won best paper honourable mentions at the ACM SIGCHI conference.