Abstract: The nature of work is being reshaped by computational systems, which increasingly draw on massive online labor markets to hire and direct workers’ behavior at scale. These crowdsourcing systems have accomplished work using pre-defined workflows, but this approach faces a fundamental limit: it can only complete tasks that are so modular and decomposable that they can be entirely pre-defined. We developed a crowdsourcing system that can achieve open-ended goals by combining the open call recruitment of crowdsourcing with the more sophisticated and reconfigurable coordination affordances of organizations. Our system creates crowd organizations, which automatically hire diverse online experts from massive online labor markets to populate computational structures inspired by organizations (roles, teams, and hierarchies), and then continuously reconfigure these structures to responsively adapt the crowd workers’ activities. We report a deployment in which crowd organizations successfully carried out open-ended product design, software development, and game production. This research demonstrates how computational systems can enable digitally networked organizations that flexibly assemble and reassemble themselves from a globally distributed online workforce to accomplish complex work.
Michael is an Assistant Professor of Computer Science at Stanford University, where he is a member of the Human-Computer Interaction group.
Melissa is an Assistant Professor at Stanford University in the Management Science and Engineering Department, and a core faculty member of the Center for Work, Technology, and Organization.