Cyber - Project - Cyber Work: The Future of Networked Labor

Cyber Work: The Future of Networked Labor

Technology has transformed from a tool that supports work into a comprehensive infrastructure that connects workers to employers. Platforms such as Uber and Amazon Mechanical Turk, which announce themselves as the “gig economy” and “paid crowdsourcing”, signal a shift where workers and employers connect ad-hoc, at large scale, to accomplish complex tasks. This shift to online networked labor has the potential to dramatically reconfigure how we shape our careers, organizations, and market platforms, and in turn shifts how those careers, organizations and platforms shape our society. Inspired by this transformation and its risks, our project addresses challenges facing the entire span of the networked labor ecosystem: individuals, organizations, and the work platform itself. We study three fundamental questions: first, how will people manage their work lives online? Second, how might organizations look in a future of networked labor? Third, how do networked labor platforms succeed? To address these challenges, we propose a combination of social scientific, design and engineering endeavors. Our efforts aim to envision the future of digital work, and to inform and create the technological platforms that enable it.

Publications:

Sharon Zhou, Melissa Valentine, Michael S. Bernstein. "In Search of the Dream Team: Temporally Constrained Multi-Armed Bandits for Identifying Effective Team Structures." CHI 2018
Daniela Retelny, Melissa Valentine, Michael Bernstein. "No Workflow Can Ever Be Enough: How Crowdsourcing Workflows Constrain Complex Work." CSCW 2018
Matt V. Leduc, Matthew O. Jackson, Ramesh Johari. “Pricing and Referrals in Diffusion Networks.” Coalition Theory Network 16.2017. http://www.coalitiontheory.net/content/pricing-and-referrals-diffusion-networks
Daniela Retelny, Michael S. Bernstein, and Melissa A. Valentine. 2017. No Workflow Can Ever Be Enough: How Crowdsourcing Workflows Constrain Complex Work. Proc. ACM Hum.-Comput. Interact. 1, 2, Article 89 (November 2017), 23 pages. https://doi.org/10.1145/3134724
Retelny, D., To, A., Rahmati, N., Doshi, T., Valentine, M.,Bernstein, M. “Flash Organizations: Crowdsourcing Complex Work by Structuring Crowds As Organizations”, CHI 2017. Winner of Best Paper Award. http://confer.csail.mit.edu/chi2017/paper#!pn2790
Michelony, A., Antonellis, I., & Johari, R. (2015). "Predicting bad job outcomes in online workplaces." Workshop on Crowdsourcing and Machine Learning (CrowdML). http://crowdml.cc/icml2015/
Bernstein, M. et al. “Crowd Guilds: Worker-led Reputation and Feedback on Crowdsourcing Platforms.” CSCW 2017. https://arxiv.org/abs/1611.01572
Hata, K. Krishna, R., Li, F., Bernstein, F. “A Glimpse Far into the Future: Understanding Long-term Crowd Worker Accuracy.” Semantic Scholar. 9/2016. https://pdfs.semanticscholar.org/d23b/1e9285d1d4b487e504d728d023d779d0ae65.pdf
Gaikwad, N.N., et al. 2016. Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms. In Proceedings of ACM Symposium on User Interface Software and Technology. ACM Press.
Salehi, N., McCabe, A., Valentine, M., Bernstein, M. Huddle: Convening Stable and Familiar Crowd Teams Despite Unpredictable Availability. 10/2016. https://arxiv.org/abs/1610.08216
Valentine, M. “Shared Responsibility and Coordination Behaviors in Temporary Teams.” 11/2016. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2872747

Researchers

http://hci.stanford.edu/msb/

Michael Bernstein

Assistant Professor of Computer Science

Michael Bernstein is an Assistant Professor of Computer Science at Stanford University, where he is a member of the Human-Computer Interaction group. His research focuses on the design of crowdsourcing and social computing systems. This work has received seven Best Paper awards and fourteen honorable mentions at premier venues in human-computer interaction. Michael has been recognized as a Robert N. Noyce Family Faculty Scholar, and has received an NSF CAREER award, Alfred P. Sloan Fellowship, and Outstanding Academic Title citation from the American Library Association. He holds a bachelor's degree in Symbolic Systems from Stanford University, and a master's and Ph.D. in Computer Science from MIT.

http://web.stanford.edu/~rjohari/

Ramesh Johari

Associate Professor of Management Science and Engineering and Computer Science (by courtesy) and Electrical Engineering (by courtesy)

Ramesh Johari is an Associate Professor at Stanford University, with a full-time appointment in the Department of Management Science and Engineering (MS&E), and courtesy appointments in the Departments of Computer Science (CS) and Electrical Engineering (EE). He is a member of the Operations Research group and the Social Algorithms Lab (SOAL) in MS&E, the Information Systems Laboratory in EE, the Institute for Computational and Mathematical Engineering, the steering committee of the Stanford Cyber Initiative, and the Stanford Bits and Watts Initiative. He received an A.B. in Mathematics from Harvard, a Certificate of Advanced Study in Mathematics from Cambridge, and a Ph.D. in Electrical Engineering and Computer Science from MIT.

https://politicalscience.stanford.edu/people/margaret-levi

Margaret Levi

Director at the Center for Advanced Study in the Behavioral Sciences

Professor of Political Science

Margaret Levi is the Director of the Center for Advanced Study in the Behavioral Sciences (CASBS) at Stanford and Professor of Political Science, Stanford University, and Jere L. Bacharach Professor Emerita of International Studies in the Department of Political Science at the University of Washington. She has been a Senior Fellow at the Watson Institute for International Studies, Brown University. She held the Chair in Politics, United States Studies Centre at the University of Sydney, 2009-13. At the University of Washington she was director of the CHAOS (Comparative Historical Analysis of Organizations and States) Center and formerly the Harry Bridges Chair and Director of the Harry Bridges Center for Labor Studies.

https://profiles.stanford.edu/melissa-valentine

Melissa Valentine

Assistant Professor of Management Science and Engineering

Melissa Valentine is an Assistant Professor at Stanford University in the Management Science and Engineering Department, and a faculty member of the Center for Work, Technology, and Organization. She conducts multi-method studies of groups and teams in organizations, with a focus on temporary teams. Her studies use longitudinal or multi-case comparisons to identify enabling conditions of fast-paced coordination in temporary teams. Recent work has focused on how crowdsourcing platforms can be used to assemble, coordinate, and adapt flash teams and flash organizations. Prof Valentine also recently published an article on how complex organizations learn, using an in-depth field study of an academic cancer center.