Edith Law

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

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.

Find out more about Edith Law at http://edithlaw.ca/.

Panos Ipeirotis

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

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 knowledge, Quizz also incorporates
questions for which we do not have a known answer; the answers given
by competent users provide useful signals for selecting the correct
answers for these questions. Quizz actively tries to identify
knowledgeable users on the Internet by running advertising campaigns,
effectively leveraging “for free” the targeting capabilities of
existing, publicly available, ad placement services. Quizz quantifies
the contributions of the users using information theory and sends
feedback to the advertising system about each user. The feedback
allows the ad targeting mechanism to further optimize ad placement.
Our experiments, which involve over ten thousand users, confirm that
we can crowdsource knowledge curation for niche and specialized
topics, as the advertising network can automatically identify users
with the desired expertise and interest in the given topic. We present
controlled experiments that examine the effect of various incentive
mechanisms, highlighting the need for having short-term rewards as
goals, which incentivize the users to contribute. Finally, our
cost-quality analysis indicates that the cost of our approach is below
that of hiring workers through paid-crowdsourcing platforms, while
offering the additional advantage of giving access to billions of
potential users all over the planet, and being able to reach users
with specialized expertise that is not typically available through
existing labor marketplaces.

Panos Ipeirotis is a Professor and George A. Kellner Faculty Fellow at
the Department of Information, Operations, and Management Sciences at
Leonard N. Stern School of Business of New York University. He
received his Ph.D. degree in Computer Science from Columbia University
in 2004. He has received nine “Best Paper” awards and nominations and
is the recipient of the 2015 Lagrange Prize, for his contributions in the
field of social media, user-generated content, and crowdsourcing.

Find out more about Panos Ipeirotis at http://www.ipeirotis.com/.

Kate Starbird

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

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 “alternative narratives” about man-made crisis events. This disinformation is often employed as part of political agendas and poses information security risks, in part through reduced trust in information systems. In this talk, I’ll present highlights from our research on alternative narratives of crisis events, describing some of the specific tactics and emergent effects of disinformation. I’ll also share some preliminary findings on more recent work examining the structure and dynamics of the media ecosystem that has taken shape around the ongoing crisis in Syria—an ongoing “site” of information warfare. Finally, I’ll discuss some of the broader implications of online disinformation for humanitarian responders, platform designers, and society at large.

Kate Starbird is an Assistant Professor at the Department of Human Centered Design & Engineering (HCDE) at the University of Washington (UW). Kate's research is situated within human-computer interaction (HCI) and the emerging field of crisis informatics—the study of the how information-communication technologies (ICTs) are used during crisis events. One aspect of her research focuses on how online rumors spread—and how online rumors are corrected—during natural disasters and man-made crisis events. More recently, she has begun exploring the propagation of disinformation and political propaganda through online spaces. Kate earned her PhD from the University of Colorado at Boulder in Technology, Media and Society and holds a BS in Computer Science from Stanford University. 

Find out more about Kate Starbird at http://faculty.washington.edu/kstarbi/.

Extreme Democracy

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

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 decisions by holding elections among models of real voters. I will focus on the computational challenges that these new paradigms give rise to. 

Ariel Procaccia is an Associate Professor in the Computer Science Department at Carnegie Mellon University. He usually works on problems at the interface of computer science and economics. His distinctions include the IJCAI Computers and Thought Award (2015), the Sloan Research Fellowship (2015), the NSF Faculty Early Career Development Award (2014), and the IFAAMAS Victor Lesser Distinguished Dissertation Award (2009); as well as half a dozen paper awards, including Best Paper (2016) and Best Student Paper (2014) at the ACM Conference on Economics and Computation (EC). He is co-editor of the Handbook of Computational Social Choice (Cambridge University Press, 2016). 

Towards a Universal Knowledge Accelerator

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

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 opportunity for accelerating this engine; instead, it threatens to slow it as the information processing limits of individual minds are reached. 

In this talk I discuss our efforts towards building a universal knowledge accelerator: a system in which the sensemaking people engage in online is captured and made useful for others, leading to virtuous cycles of constantly improving information sources that in turn help people more effectively synthesize and innovate. Approximately 70 billion hours per year in the U.S. alone are spent on complex online sensemaking in domains ranging from scientific literature to health; capturing even a fraction of this could provide significant benefits. We discuss three integrated levels of research that are needed to realize this vision: at the individual level in understanding and capturing higher order cognition; at the computational level in developing new interaction systems and AI partners for human cognition; and at the social level in developing complex and creative crowdsourcing and social computing systems.

Aniket Kittur is an Associate Professor and holds the Cooper-Siegel Chair in the Human-Computer Interaction Institute at Carnegie Mellon University. His research looks at how we can augment the human intellect using crowds and computation. He has authored and co-authored more than 70 peer-reviewed papers, 14 of which have received best paper awards or honorable mentions. Dr. Kittur is a Kavli fellow, has received an NSF CAREER award, the Allen Newell Award for Research Excellence, major research grants from NSF, NIH, Google, and Microsoft, and his work has been reported in venues including Nature News, The Economist, The Wall Street Journal, NPR, Slashdot, and the Chronicle of Higher Education. He received a BA in Psychology and Computer Science at Princeton, and a PhD in Cognitive Psychology from UCLA.