Managing personal information with private, accountable crowdsourcing
- Crowd-powered systems combine the power of human judgment and creativity with the speed and precision of computers. These systems can efficiently help people be more productive in ways that no single human assistant or computer program could accomplish alone. To provide help with personal information management, crowd-workers need access to people's personal information. However, people are understandably reluctant to share their entire private dataset with online workers. I introduce privacy and accountability techniques for parsimoniously sharing private data with online workers and provide experimental evidence that people can be more productive with assistance from the crowd. These techniques develop crowdsourcing as a platform trustworthy and responsive enough to be integrated into personal information management. This thesis develops these ideas through two crowd-powered systems. The first, TaskGenies, is a task list that automatically breaks down users' tasks into actionable steps that can be completed one at a time. These action plans are created through crowdsourcing and reused through natural language processing when possible. The second system, EmailValet, is a web-based email client that introduces valet crowdsourcing. With EmailValet, users can share a limited subset of their inbox with online human assistants who extract embedded tasks from these emails. The system mediates and logs assistant access to establish accountability. These systems point to a future in which people are personally empowered by the crowd and people's private data can be entrusted to crowdsourcing.
|Type of resource
|electronic; electronic resource; remote
|1 online resource.
|Kokkalis, Petros Nicolas
|Stanford University, Department of Electrical Engineering.
|Lam, Monica S
|Lam, Monica S
|Statement of responsibility
|Petros Nicolas Kokkalis.
|Submitted to the Department of Electrical Engineering.
|Thesis (Ph.D.)--Stanford University, 2013.
- © 2013 by Petros Nicolas Kokkalis
- This work is licensed under a Creative Commons Attribution Non Commercial No Derivatives 3.0 Unported license (CC BY-NC-ND).
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