How to Incentivize Data-Driven Collaboration Among Competing Parties

The availability of vast amounts of data is changing how we can make medical discoveries, predict global market trends, save energy, and develop new educational strategies. In certain settings such as Genome Wide Association Studies or deep learning, the sheer size of data (patient files or labeled examples) seems critical to making discoveries. When data is held distributedly by many parties, as often is the case, they must share it to reap its full benefits. One obstacle to this revolution is the lack of willingness of different entities to share their data, due to reasons such as possible loss of privacy or competitive edge. Whereas cryptographic works address the privacy aspects, they shed no light on individual parties’ losses and gains when access to data carries tangible rewards. Even if it is clear that better overall conclusions can be drawn fom collaboration, are individual collaborators better off by collaborating? Addressing this question is the topic of this paper. ...

• Type: Journal
• Year: 2016
• Where: INNOVATIONS
• Authors: Pablo Daniel Azar, Shafi Goldwasser, Sunoo Park
• Keywords: INNOVATIONS 2016