Saturday, January 30, 2016

The other side of Big Data

This will sort of be my off-day post because it's sort of an off day. I worked late last night and some more today monitoring some jobs that run long.

I'm currently the subject in a trial that, presumably, has some Big Data implications (though I have no idea what those are). For obvious reasons, the research department at work is interested in fitness trackers. My understanding is that the correlation between fitness and life expectancy is very weak (the quality of life may be better, but actual longevity is what a Life Insurer cares about). The hope is that some better correlating variables can be found with the use of the latest generation of fitness trackers.

So, lot's of folks at work are wearing fitness trackers for the next month and a half. I got a Basis Peak. On the surface, it's an exceedingly cool little device. The screen is like that of a smartwatch (actually, since it pairs to your phone, I guess it qualifies as a smartwatch). The user interface is reasonably intuitive and the touchscreen is a nice mix of responsive without being twitchy.

Underneath the skin, I'm less convinced. On my run this morning, it had my heart rate varying all over the place. In reality, it was quite steady (as one would expect on an easy run with a group). The distance measured was also a bit short. It did seem to do a pretty good job of counting my strides. It collected lots of other data, too, but I have no idea how to interpret that.

Truth is, I don't really care. I know what running easy is supposed to feel like. I know what tempo pace feels like. I know what marathon pace feels like. I really don't need a device of any kind to run a desired pace. A few years back, I ran the St. Louis Track Club pace series. It's 16 "races" where your finish time is the absolute difference between your projected and actual time. In other words, if you say the 5K will take you 19:30 and you run it in 19:45, your "finish" time is 15 seconds. Obviously, you're not allowed to wear a watch during the run. My total for the series (best 3 out of 4 in a month count, so 12 total) was under two minutes. And if you think that's good, yes, it was (third overall if I recall correctly), but the series winner was half that. Good runners have pacing dialed in pretty tight.

Anyway, some of the variance I was seeing could well be user error. I just started using this thing yesterday and may well not have the strap tight enough or something else set up wrong. Regardless, it's information I just don't need and I'm not really a gadget geek so, cool as it is, I won't be running out and buying one when this study is over.

Now, what I would like to know is what they are doing with the data? Of course, it's anonymous (and, I wouldn't care if it wasn't - there's nothing about my fitness that I need to keep secret). What I mean is how is this going to help them make more money on life insurance My guess is that, since people are so willing to post this stuff on publicly available sites, they want to make special rate offers to folks they can identify as very good risks. It's illegal to ask for this sort of information, but if somebody wants to volunteer it, using it is fair game. Google is doing the same thing getting into car insurance (hint: if you get pissed at the driver who cuts you off, don't post that on Facebook; your insurance company WILL find out about it sooner or later and classify you as having potential for road rage).

It's far enough from my thesis topic that my interest is purely curiosity, but it's still a question I will bother to ask.

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