Large-Scale Collaborative Innovation: Challenges, Visions and Approaches

Siangliulue, Pao (Harvard University) | Chan, Joel (Carnegie Mellon University) | Arnold, Kenneth C. (Harvard University) | Huber, Bernd (Harvard University) | Dow, Steven P. (Carnegie Mellon University) | Gajos, Krzysztof Z. (Harvard University)

AAAI Conferences 

Emerging online innovation platforms have enabled large groups of people to collaborate and generate ideas together in ways that were not possible before. However, these platforms also introduce new challenges in helping their members to generate diverse and high quality ideas. In this paper, we enumerate collaboration challenges in crowd innovation: finding inspiration for contributors from a large number of ideas, motivating crowd to contribute to improve group understanding of the problem and solution space, and coordinating collective effort to reduce redundancy and increase quality and breadth of generated ideas. We discuss possible solutions to this problem and present our recent work that addresses some of these challenges using techniques from human computation and machine learning.

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