Title: Volunteer-Based Online Experiments With Diverse Samples: Lessons Learned from Six Years of LabintheWild Speaker: Katharina Reinecke, Assistant Professor of Computer Science & Engineering, University of Washington Date: May 1, 2018 Time: 12:00-1:00pm Room: Gates-Hillman Complex 6501 Abstract: An estimated 95% of our scientific knowledge about people, their behavior, perception, and preferences is based on studies with “WEIRD” samples, an acronym for participants who are Western, Educated, Industrialized, Rich, and Democratic. My work in Human-Computer Interaction has shown that tech ..read more

Title: Socio-technical Challenges in Scientific and Medical Crowdsourcing Speaker: Edith Law, Assistant Professor in Computer Science, University of Waterloo Date: April 17, 2018 Time: 12:00-1:00pm Room: Gates-Hillman Complex 6501 Abstract: 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 ..read more

Title: Targeted Crowdsourcing with a Billion (Potential) Users Speaker: Panos Ipeirotis, Professor in Department of Information, Operations, and Management Sciences at NYU Stern School of Business Date: April 10, 2018 Time: 12:00-1:00pm Room: Gates-Hillman Complex 6501 Abstract: We describe Quizz, a gamified crowdsourcing system that simultaneously assesses the knowledge of users and acquires new knowledge from them. Quizz operates by asking users to complete short quizzes on specific topics; as a user answers the quiz questions, Quizz estimates the user’s competence. To acquire new knowledg ..read more

Title: Muddied Waters: Online Disinformation during Crisis Events  Speaker: Kate Starbird, Assistant Professor in Human-Centered Design and Engineering, University of Washington Date: March 20, 2018 Time: 12:00-1:00pm Room: Newell-Simon Hall 1305 Abstract: Since 2013, my collaborators and I have conducted research on how rumors and misinformation spread through social media during crisis events. Recently, our work has revealed how a subsection of the alternative media ecosystem facilitates the spread of disinformation—in the form of conspiracy theories or “alter ..read more

Title: Extreme Democracy  Speaker: Ariel Procaccia, Associate Professor in Computer Science, Carnegie Mellon University Date: December 12, 2017 Time: 12:00-1:00pm Room: Gates-Hillman Center 6501 Abstract: I will present several forms of democratic decision making that go far beyond your run-of-the-mill election. Specifically, I will discuss (i) liquid democracy, which allows voters to transitively delegate their votes; (ii) participatory budgeting, in which residents of a city or country vote on how its budget should be divided; and (iii) virtual democracy, which automates ethical decis ..read more

Title: Towards a Universal Knowledge Accelerator Speaker: Aniket Kittur, Associate Professor in Human-Computer Interaction Institute, Carnegie Mellon University Date: October 17, 2017 Time: 12:00-1:00 Room: Gates-Hillman Center 6501 Abstract: The human mind remains an unparalleled engine of innovation, with its unique ability to make sense of complex information and find deep analogical connections driving progress in science and technology over the past millennia. The recent explosion of online information available in virtually every domain should present an opportu ..read more

Title: Learning from People Speaker: Nihar B. Shah, Assistant Professor in Machine Learning and Computer Science, Carnegie Mellon University Date: October 10, 2017 Time: 12:00-1:00pm Room: Gates-Hillman Complex 6501 Abstract: Learning from people represents a new and expanding frontier for data science. Two critical challenges in this domain are of developing algorithms for robust learning and designing incentive mechanisms for eliciting high-quality data. In this talk, I describe progress on these challenges in the context of two canonical settings, namely those of ranking and cla ..read more

Title: Solving Photo Mysteries with Expert-Led Crowdsourcing Speaker: Kurt Luther, Department of Computer Science, Virginia Tech Time: 12:30 - 1:30pm Room: Gates-Hillman Complex 6501 Abstract: Despite the old adage that a picture is worth a thousand words, images often need context to be meaningful to their viewers. In this talk, I show how expert-led crowdsourcing, a novel approach that combines the relative strengths of experts and amateur crowds, can be used to solve photo mysteries. In one example, I conducted a qualitative study of image verification experts in journalism, national ..read more

Title: Supporting Collective Ideation at Scale Speaker: Pao Siangliulue, Department of Computer Science, Harvard University Date: April 18, 2017 Time: 12:30 - 1:30pm Abstract: A growing number of online collective ideation platforms, such as OpenIDEO or Quirky, have demonstrated the potential of large-scale collaborative innovation in various domains. However, these platforms also introduce new challenges. People have to wade through a sea of possibly mundane and redundant ideas before encountering genuinely inspiring ones. Further, once all ideas are collected, the communities have to spend ..read more

Title: The Collaboration and Communication Networks within the Crowd Speaker: Siddharth Suri, Microsoft Research, New York City Time: 12:30-1:30pm Room: Newell-Simon Hall 1507 Title: The Collaboration and Communication Networks within the Crowd Abstract:  Since its inception, crowdsourcing has been considered a black-box approach to solicit labor from a crowd of workers. Furthermore, the crowd has been viewed as a group of independent workers dispersed all over the world. One goal of this work is to show that crowdworkers collaborate to fulfill technical and soci ..read more