The name of workshop participants are bolded.
Sally A. Applin, Michael D. Fischer
University of Kent
Cooperating with Algorithms in the Workplace
Biography: Sally A. Applin is a Doctoral Candidate in Anthropology at the University of Kent at Canterbury, UK, working with the Centre for Social Anthropology and Computing (CSAC) where she researches the impact of technology on culture, Maker culture, leading technologies, and the outcomes of network complexities as modeled by PolySocial Reality (PoSR). Sally holds a Masters degree from the graduate Interactive Telecommunications Program at NYU (ITP), and a BA in Conceptual Design from SFSU. Sally has had a 20+ year career in the science museum design, computer software, telecommunications, and product design/definition industries working as a Senior UX Designer, Senior Consultant and Ethnographer. Sally is a founding member of AnthroPunk, a movement that examines how people promote, manage, resist and endure change, as well as an Associate Editor of the IEEE Consumer Electronics Magazine (Societal Impacts Section), a board member of the Edward H. and Rosamond B. Spicer Foundation, and a member of IoT Council, a think tank for the Internet of Things.
Scott Allen Cambo, Darren Gergle
Interactive Active Learning for Understanding Workplace Systems And The Potential Problems They Invite
Shuo Chang, Peng Dai*, Lichan Hong*, Cheng Sheng*, Tianjiao Zhang*, Ed H. Chi*
University of Minnesota
Google Inc. *
Paper: AppGrouper: Knowledge-graph-based Interactive Clustering Tool for Mobile App Search Results
Biography: Shuo Chang is a fifth year PhD student in Computer Science Department at University of Minnesota, supervised by Prof. Loren Terveen. His research interest lies in the interaction between human and AI: (1) analyze users’ behavior in online communities and personalize their experience with machine learning (Recommender system); (2) leverage crowd wisdom to improve machine learning systems. Shuo has industry experience in Google Research and eBay research labs, working as research intern on social computing and recommendation technology. Shuo graduated from Chu Kochen Honors college at Zhejiang University.
Paper: Algorithmic Reflexivity or Algorithmic Oversight? Shaping the Normative Futures of Data-Driven Work
Biography: I am a scholar of work and am currently conducting research that interrogates the connections between digital infrastructures, work practices, and emerging professional norms. I received my PhD from the Center for Work, Technology, and Organization in the Department of Management Science and Engineering at Stanford University in 2009. Currently I am an Assistant Professor in the Department of Library and Information Science at Rutgers University.
In addition to teaching an undergraduate course on social informatics, which typically includes a unit on big data and algorithms, I am also in charge of developing a concentration on ‘Technology, Information & Management’ (TIM) in our department’s newly revised Master of Information program. Within this concentration, I am responsible for teaching several applied management courses, including project management and knowledge management, but in the future I plan to develop a course in line with the themes of this workshop—a close look at the role data and algorithms will (and are already are) playing in contemporary forms of knowledge work.
R. Stuart Geiger
University of California, Berkeley
Paper: Administrative support bots in Wikipedia: how algorithmically-supported automation can transform the affordances of platforms and the governance of communities
For PDF, please email the author (stuart [at] stuartgeiger.com)
Biography: R. Stuart Geiger is an ethnographer and post-doctoral scholar at the Berkeley Institute for Data Science at UC-Berkeley, where he studies the infrastructures and institutions that support the production of knowledge. His Ph.D research at the UC-Berkeley School of Information focused on the governance and operation of Wikipedia and scientific research networks. He has studied topics including newcomer socialization, moderation and quality control, specialization and professionalization, cooperation and conflict, the roles of support staff and technicians, and diversity and inclusion. He uses ethnographic, historical, qualitative, and quantitative methods in his research, which is grounded in the fields of Computer-Supported Cooperative Work, Science and Technology Studies, and communication and new media studies.
David Lee, Ashish Goel
Paper: Small groups as building blocks for crowd algorithms: mitigating the human-algorithm tension
Biographies: David T. Lee is a Ph.D. Candidate at Stanford University in the Social Algorithms Lab and Crowdsourced Democracy Team. His current research centers around algorithms, platforms, and incentives for a participatory democracy. He is a recipient of the NSF Graduate Research Fellowship, an Accel Innovation Scholar, and twotime recipient of the Brown Institute for Media Innovation Magic Grant. He was a coauthor on a paper which received the notable paper award at HCOMP 2014.
Ashish Goel is a Professor of Management Science and Engineering and (by courtesy) Computer Science at Stanford University, and a member of Stanford’s Institute for Computational and Mathematical Engineering. His research interests lie in the design, analysis, and applications of algorithms; current application areas of interest include social networks, participatory democracy, Internet commerce, and large scale data processing. Professor Goel is a recipient of an Alfred P. Sloan faculty fellowship (200406), a Terman faculty fellowship from
Stanford, an NSF Career Award (200207), and a Rajeev Motwani mentorship award (2010). He was a coauthor on the paper that won the best paper award at WWW 2009, and an Edelman Laureate in 2014. Professor Goel was a research fellow and technical advisor at Twitter, Inc. from July 2009 to Aug 2014.
Moira McGregor, Airi Lampinen, Barry Brown
Paper: Platform Labour: Algorithms Versus Business Ethics
Biographies: Moira McGregor is a PhD candidate at Mobile Life Centre, Stockholm University, Sweden. Her research looks at technology use in everyday life – from mobile phones in co-present interaction, to how an app like Uber impacts the work practices of its users.
Airi Lampinen (PhD, University of Helsinki) is a Postdoctoral Researcher at Mobile Life Centre, Stockholm University in Sweden. Her research focuses on interpersonal boundary regulation in social network services and in the so-called sharing economy.
Barry Brown is Professor of Human Computer Interaction at Stockholm University, Sweden, and research director of Mobile Life Research Centre.
Samir Passi, Phoebe Sengers
Paper: “From what I see, this makes sense:” Seeing meaning in algorithmic results
Biographies: Samir Passi joined Cornell University in 2013 as a Ph.D. student in Information Science at Cornell University to work with Phoebe Sengers, Steve Jackson, and Malte Ziewitz. His research interests lie primarily at the intersection of Information Science and Science & Technology Studies. In his work – situated within social studies of data analysis – he looks at how people work with and through machines to make sense of data. Samir has a research masters in Science & Technology Studies from Maastricht University, The Netherlands, and an undergraduate degree in Information & Communication Technology engineering from DA-IICT, India.
Phoebe Sengers is a faculty member in Information Science and Science & Technology Studies at Cornell University, where she leads the Culturally Embedded Computing group. Her work integrates analysis of the political and social impacts of technology with IT design. Her primary current focus is a long-term design-ethnographic and historical study of sociotechnical change in the small, traditional fishing community of Change Islands, Newfoundland, looking at how changing sociotechnical infrastructures are tied with changing orientations to time, technology, and labor. Phoebe graduated from Carnegie Mellon University in 1998 with a self-defined interdisciplinary Ph.D. in Artificial Intelligence and Cultural Theory.
Alex Rosenblat, Karen Levy*, Solon Barocas**, Tim Hwang
Data & Society Research Institute
Cornell University *
Microsoft Research **
Paper: Discriminating Tastes: Customer Ratings as Vehicles for Bias
[Oct. 2016: The above paper is an updated version of original workshop submission “Uber’s Pax: Hidden Bias in Rating Systems”]
Biography: See below.
Alex Rosenblat, Luke Stark*
Data & Society Research Institute
New York University *
Paper: Uber’s Drivers: Information Asymmetries and Control in Dynamic Work
Biographies: Alex Rosenblat is a researcher and technical writer at Data & Society. Her areas of research include socio-technical systems, the intersection of technology and labor, and the social and civil rights implications of emergent technologies, such as police body-worn cameras. She currently examines the relationship between semi-automated systems and labor management, with a particular focus on the on-demand economy. She holds an MA in Sociology from Queen’s University in Canada, and a BA in History from McGill University.
Luke Stark is doctoral candidate in the Department of Media, Culture, and Communication at New York University under the supervision of Helen Nissenbaum. His dissertation project, “Self-Managed Feeling: Psychology and Interaction Design from Smartphones to the Anxious Seat,” is a genealogy of digital mood tracking applications, and explores how psychological tools and techniques have been built into the design of the mobile device we use on a daily basis. With a focus on affect and emotion, Luke’s broader scholarship explores the changing nature of human subjectivity in the computational age. Luke holds an Honours BA in History & English and an MA in History, both from the University of Toronto; he has been generously funded by the National Science Foundation, New York University’s Steinhardt School of Culture, Education, and Human Development and the Provost’s Global Research Initiative, the Intel Science and Technology Center for Social Computing, and Microsoft Research.