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Telling Traces

Location: Ballroom III - VI Level: Novice
Average rating: ***..
(3.88, 8 ratings)

Mobile smartphones can be easily programmed to automatically record GPS coordinates and accelerometer readings, creating geocoded, time-stamped, activity logs of our every day lives. When combined with the wealth of spatial data and models available on the web these activity traces can be used to make strong inferences. Moreover, even the simplest mobile phone can be used to capture time-stamped self-reported data; and, when supported by web-based applications to prompt, capture, and curate, these “tweets with a purpose” can create traces of your vital signs, medical symptoms, mood, eating habits, etc. Unlike much of the data captured by third party services and surveillance systems, our activity and self-report traces are already personally identified, legally reusable and releasable by the individual, and very easily processed. We have the opportunity to learn so much more about ourselves, at close to zero marginal cost. While it is true that since the pervasive adoption of credit cards, automatically-generated traces of our lives have been gathered, by and large this learning has not been easily actionable by individuals and the data (for better, not worse) has been used primarily by the collecting institutions. With the broad adoption of mobile phones and easily leveraged web/cloud services, we have the opportunity to capture, process, and learn from our own traces. In this talk Deborah will describe promising applications and suggest that it’s time to consider the technical and legal structures needed for individuals to retain control over their telling traces.

Photo of Deborah Estrin

Deborah Estrin

Cornell NYC Tech

Deborah Estrin is a Professor of Computer Science at the new Cornell Tech campus in New York City and a Professor of Public Health at Weill Cornell Medical College. She is co-founder of the non-profit startup, Open mHealth. She was previously on faculty at UCLA and Founding Director of the NSF Center for Embedded Networked Sensing (CENS).

Estrin is a pioneer in networked sensing, which uses mobile and wireless systems to collect and analyze real time data about the physical world and the people who occupy it. Estrin’s current focus is on mobile health (mhealth), leveraging the programmability, proximity, and pervasiveness of mobile devices and the cloud for health management. She is an elected member of the American Academy of Arts and Sciences and the National Academy of Engineering.