So earlier this week, Dave and I were published in a lifetracking/streaming article (thanks to sweet friends Brynn and Chris) in the Washington Post called Bytes of Life. We thought our conference call with reporter Monica Hesse went pretty well, but neither of us expected to get the kind of coverage we did for talking about a little statistics app we’re working on that we’ve tentatively called I Did Stuff, which is basically a combination of every good idea we’ve had in the last year.
The premise for I Did Stuff lies in the belief that we’re tracking so many aspects of our life now that computers need to not only make sense of this data for our own use, but also use it to deliver status on demand. One common example I’ve used is that of the “reverse twitter”…basically to combine Google calendar, IM status, and whole host of other data sources into one remotely queryable interface. And anyone can ask this interface “Where is Dave?” and receive a response like “Well he isn’t in front of IM, but he has class in 10 minutes, so he might be in transit. But his phone is on the charger, so he either forgot his phone or is oversleeping.”
Which was a great idea a year ago, and as far as I know still hasn’t been done. But since then, this idea has grown into so much more. Not only do we want to create an AI who can infer status for others, we want it to learn more about us than we know ourselves.
A few months ago I decided to try a little experiment, which was inspired by a conversation with Tantek in which he stated that RSS feeds aren’t even a part of his personal communication stack…everything he needs to know he hears from his social graph via twitter. Frustrated that I had just declared RSS bankruptcy, I wondered if I was spending too much time keeping up with what other people were doing…time that could instead be invested into bringing my own ideas to fruition. Although all blogs other than those of a few close friends were cut out of my daily reads, what came to be known as the TechCrunch Experiment was born. And although initially liberating, I quickly found that my particular social graph wasn’t feeding me enough of the right kind of data items to keep me motivated; after a few months, I found my new idea generation rate (or at least my idea improvement rate) went almost to zero. My creative juices ran dry when operating in an RSS free vacuum.
This makes sense because I then realized I build my Twitter contacts around keeping up with peoples’ lives, and had built my RSS feeds around keeping up with news. So even though I didn’t end up being able to save time, I’d say it’s still pretty good to know what fuels you, right?
For a more recent example (recent = correlated today), I occasionally have a problem with not eating. More along the lines of forgetting to rather than an eating disorder, but we all have our vices. I’ll not eat well for a few days and get lethargic and depressed and wonder wtf is wrong. Now this sounds like a fairly simple correlation, but with everything else going on in life it can be hard to notice if you’re not paying close attention. So I today I purchased a cheap glucose monitor (along with not-so-cheap test strips, jeez) to track this one dimension of how my diet affects my energy and moods. All I’ve learned over the past 24 hours is that I just need to EAT, but seeing concrete evidence of this reinforces the consequence of my actions, plus gives me a scale to rate how well I’m doing.
Something like this could be tracked in the personal unit testing system, but the value in this data is more than just binary passing or failing. Lifetracking, lifestats, personal informatics, lifestreaming 2.0…call it what you will, these are MBO’s for life.
These examples represent only a few possibilities, just imagine how many factors influence your mood and performance! Diet, weight and exercise, weather, what time you went to bed, where you are, who you’re spending time with, the projects you’re working on, your social connections (and growth rate), what blogs you’re reading, the music you’re listening to, what applications you’re using, the conferences you’re going to, how long it is until payday…or if you’re Brynn and Chris, the last time you had sex.
This data is already being recorded, we just need a smarter way to use it.
Which is, as they say, a bigger algorithm.