WearMail
Saiganesh Swaminathan, Raymond Fok, Fanglin Chen, Ting-Hao Huang, Irene Lin, Rohan Jadvani, Walter S. Lasecki, Jeffrey P. Bigham · 2017
Email is more than just a communication medium. Email serves as an external memory for people---it contains our reservation numbers, meeting details, phone numbers, and more. Often, people need access to this information while on the go, which is cumbersome from mobile devices with limited I/O bandwidth. In this paper, we introduce WearMail, a conversational interface to retrieve specific information in email. WearMail is mostly automated but is made robust to information extraction tasks via a novel privacy-preserving human computation workflow. In WearMail, crowdworkers never have direct access to emails, but rather (i) generate an email filter to help the system find messages that may contain the desired information, and (ii) generate examples of the requested information that are then used to create custom, low-level information extractors that run automatically within the set of filtered emails. We explore the impact of varying levels of obfuscation on result quality, demonstrating that workers are able to deal with highly-obfuscated information nearly as well as with the original. WearMail introduces general mechanisms that let the crowd search and select private data without having direct access to the data itself.