Ethical Lifelogging (is it?)
I’ve logged my life for more than ten years now. Some of the data were collected semi-locally, meaning I used tools that collected them on and wrote them to a storage device of my own. But most weren’t. My activity data is logged by an Apple device and stored in their cloud. My electronic scale sends data to Withings/ex-Nokia, my diet is logged and stored by MyFitnessPal, videos and photos land on Apple’s servers as well.
And that’s just the beginning. My medical data is often kept hostage by whomever logged it, sold for a pretty ransom every time I want to access it. Even things such as my blood glucose readings were, for a long time, property of Abbot Medical who made it impossible to get them out. This has changed with the addition of xDrip4iOS to my repertoire, but still, there’s 2015-2021 data somewhere on a soulless health company’s servers.
Sure, I could circumvent all this. I could prick my finger every five to ten minutes, write down data into an old FieldNotes notebook, and spend my evenings calculating the results.
I could step onto an old scale, do the same. Write down my food every day and use flashcards containing caloric calculations I did the first time I ate that thing. I could have a friend take my blood pressure three times a day, note that down, too.
And then, at the end of the day, plug everything into a LibreOffice document or Rstudio spreadsheet and get my analysis.
Thing is, though… lifelogging doesn’t work if it takes over your life. My watch, without my doing much, logs my moves, temperature, O2 saturation, stride length, stair climbing speed, gait, and more. It just does. And it tells the time and buys me coffee.
My FreeStyle Libre grabs my blood glucose every five minutes. My scale tattles on me and my shitty diet, and my HomePod logs temperature, noise, and humidity over night to correlate with my AutoSleep sleep patterns.
While all this is transparent and effortless to me, it also turns me transparent to third parties. In 2007 Fitbit, then a standalone company and not part of Google, sent a dozen of its first exercise trackers to the BodyHacking community in San Francisco. We all installed the (very beta) app and used it extensively. Until one of the participants found out the hard way, that “sexual activity, vigorous, 42 minutes” wasn’t just a private entry, everyone on her friends list, her mother included, could see it. And that it was impossible to delete individual data points without cancelling one’s account and paying for a new one.
Now, me, I know what I am getting myself into. I know Google tracks my every move using EXIF data of all those photos auto-uploaded into its Google Photos cloud, Apple knows better than me when I had sex, and Withings probably sells my weight loss journey data to advertisers trying to get me to buy new and revolutionary ways to “shed the pounds and keep them off.”
I’m OK with all that. It’s the hefty price I pay for data that, extracted and collated, helps me body hack myself.
But my patients don’t. They do not understand, that using the fancy blood pressure meter with bluetooth and app support also feeds their data to a company in China which, in turn, hides a few lines about selling that data to third parties in their TOS.
So I am torn. On one hand, I’d love for my patients to wear Freestyle Libre sensors and get me the truth, the whole truth, and nothing but the truth rather than whatever blood glucose readings they were able and willing to take. I’d love for my elderly to use bluetooth connected pill boxes that show compliance and allow me to counsel on strategies to get that life-saving β-blocker into them at the right time, every time.
On the other hand, I am sworn to do no harm. And harm comes from transparency that is not marked as such.
We urgently need cheap, useful, useable, and widely available tech that does what Google, Apple, Withings, Abbott, Dexcom, and others do today. Without data lock in, without backend analysis, and without forcing physicians to pay more than a months worth of income to liberate that locked in data.