Human computation tasks with global constraints

Authors:
Haoqi Zhang;Edith Law;Rob Miller;Krzysztof Gajos;David Parkes;Eric Horvitz
Affiliations:
Harvard University, Cambridge, Massachusetts, United States;Carnegie Mellon University, Pittsburgh, Pennsylvania, United States;MIT CSAIL, Cambridge, Massachusetts, United States;Harvard University, Cambridge, Massachusetts, United States;Harvard University, Cambridge, Massachusetts, United States;Microsoft Research, Redmond, Washington, United States
Venue:
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Year:
2012

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Abstract

An important class of tasks that are underexplored in current human computation systems are complex tasks with global constraints. One example of such a task is itinerary planning, where solutions consist of a sequence of activities that meet requirements specified by the requester. In this paper, we focus on the crowdsourcing of such plans as a case study of constraint-based human computation tasks and introduce a collaborative planning system called Mobi that illustrates a novel crowdware paradigm. Mobi presents a single interface that enables crowd participants to view the current solution context and make appropriate contributions based on current needs. We conduct experiments that explain how Mobi enables a crowd to effectively and collaboratively resolve global constraints, and discuss how the design principles behind Mobi can more generally facilitate a crowd to tackle problems involving global constraints.