“Our Data, Ourselves”
by Kate Greene
Discover, December 2011
[Greene notes: I had originally sent an almost identical pitch to Technology Review, where I was formerly an editor, but a staff editor was working on a feature that was similar. TR suggested I do an 800 word profile of Bob Evans as a side bar, but I felt like his story needed more space, so I declined the offer. At this point, I didn’t have a guarantee that I could place the story anywhere, but I had been wanting to write for Discover. I also knew that my access to a Google engineer was something special, so there could be a good chance that another publication would pick it up. In sending it to Discover, I modified the pitch slightly, suggesting at the end that I’d be willing to approach the story from different perspectives, including one in which I would test out the self-tracking lifestyle.
Another important change was the addition of a personal introduction. My only connection to the magazine was a tenuous one: I was an intern candidate in 2005, which led to a conversation with Corey Powell, the managing editor at the time. In the pitch, I re-introduced myself in the first paragraph and reminded him of our fleeting conversation five and a half years before. He passed it along to senior editor Eric Powell (no relation), and after a few conversations about story-telling approach and reporting logistics, Eric assigned it to me.
The story based on this pitch ran in the December issue of Discover. It’s slightly different than the story I originally conceived. During my reporting, it became clear that the angle on bringing self- tracking to the masses should be played down as the project wasn’t going to have as large a launch and impact as Evans had expected. Also the Quantified Self conference that I proposed as a peg was absorbed into general reporting and didn’t come out in the final story. But the essence is all there. I’m grateful to Discover for taking a chance on a new writer. And I’m grateful to Evans at Google for giving me unprecedented access to his project. The story couldn’t have come off as it did without it.]
It’s Kate Greene, a Discover intern candidate from 2005. I went by Katie Greene then, and ended up at Science News for that interning term, but I remember we exchanged a number of emails
and a nice phone conversation over the course of the selection process. Well, fast forward 5.5 years, and you’re the EiC, and I’m a freelancer with about four years of editing/writing from Technology Review under my belt.
My point: I’m interested in writing for Discover, and I have a feature idea that I hope interests you.
My pitch: Personal Data Mining, by Google
I’ve been talking to a researcher at Google who’s developed a personal data-mining app for iPhone and Android that the company has been using internally for about a year. The app, called PACO, does essentially what Nathan Eagle (founder of the startup txteagle) and MIT prof Sandy Pentland’s reality mining phones did back in 2005 (http://reality.media.mit.edu/): it collects a person’s whereabouts, interactions, activity, feelings and sentiments, and makes sense of them-
-giving a person a quantitative view of herself. But unlike an academic project, PACO has the potential to reach the public.
The Google researcher, Bob Evans, is in the engineering productivity department, and has purposely designed the app to be customizable. You can use PACO to write your own “experiments” like an app that tracks your allergy symptoms and correlates it to weather forecasts and pollen counts. You could use it to make your own RunKeeper, diet, mood, or sleep tracker. Human resources departments could use PACO to write employee surveys that ask questions throughout the day or week, getting a more accurate read on what makes specific people and teams productive. Scientists could use the app to build surveys that collect instant sentiment or real-time data, solving the problem of inaccurate recall from which most surveys suffer.
Privacy is a big deal to Evans and he explained to me that the phone is a unique platform for behavior monitoring because it’s with you all the time and everything can be stored, securely, on the device. If a person chooses to backup their data to a server, or to participate in a broader experiment in which they share their data, the information is encrypted and anonymous.
Of course, privacy experts might scoff at the idea anyway–Google controls so much of the world’s information and now it wants intimate personal data? But Evans sees no reason for Google to store and mine this information. Rather, he wants to give people the tools to do it themselves. It’s an idealistic approach that will be interesting to watch evolve.
The time peg for this piece is the Quantitative Self Conference in Mountain View, May 28-29. These quantified self folks have been tabulating their daily habits for years, but they often use a piecemeal approach, cobbling together apps, using spreadsheets, and forming support groups to talk about their sleep problems, among other personal details. Evans plans on presenting PACO at the conference–I think this could really revolutionize the way this fringe group collects their self-data, but I think it could also be the true birth of practical, personalized reality mining.
I see a narrative unfolding in a few different ways. One, I could use the app to get to know myself better, figuring out ways to improve my productivity just as the test Googlers have. The background story of the quantified-self movement, the MIT research, and Evans’ developing the all-seeing app would be interwoven here. Or, vice versa. The main story could be Evans
developing the app internally for Google, interwoven with background on the QS movement and my personal story of self discovery. Or, I could take myself out of it completely. I’m open to hashing out the story structure with you if you’re interested in the topic.
Also, I hope you’re doing well! I’ll be in NYC in the summer and would love to stop by and meet you properly.
All the best, Kate