
This article is part of a continuing series about data collection today. The previous articles talked about devices in your home and your car; now we’ll get more personal.
The data collected by fitness devices occupies an ambiguous place on the privacy spectrum. The data doesn’t contain information that can obviously cause harm, such as your social security number or passwords. On the other hand, no data about individuals is more sensitive.
An elderly relative of mine was told by her Apple Watch that her heart was racing. The watch advised her to see her doctor right away. Luckily, she could get appointments quickly and ended up on medication for atrial fibrillation. This is a simple example of how devices can deduce a lot of personal information.
Analytics to detect early signs of dementia and depression in people’s voices are in experimental stages. Depression can also be detected in people’s manner of walking.
I consulted two sites to find out the data collected by the Apple Watch, one site aimed at consumers and a more complete list aimed at developers. The information that your watch knows about you is pretty extensive:
Like automobile companies, Apple supplements this information with other things that you voluntarily tell it in order to enhance its fitness evaluations, or that it knows about you (such as your Apple store downloads).
I returned to the Mozilla Foundation for their assessment of privacy risks in the Apple Watch. They praise Apple’s policies but warn that, like any computer, the watch and the data storage behind it might have vulnerabilities.
I then searched around for information collected by another popular device, the Fitbit. Its main devices are a 3-axis accelerometer (measuring motion forward/backward, to the side, and up/down) and a GPS. Through one fitness site and Google’s Fitbit Help Center, I accumulated the following list:
When tracked over time, these statistics (supposedly) say a lot about your health, behavior, and lifestyle.
The next article in this series goes online and discusses data collection on the Web.
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