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One unexpectedly great application for Apple Watch: stochastic self-sampling. e.g. here's my mental energy level throughout the day. Can use notification actions to respond in one tap, so it's low-friction enough for 10+ prompts per day; and works when away from computer.
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That's >500 data points over the past couple months. Hard to imagine collecting that if I had to remember to diary, or even if it required pulling out my phone.
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At least for me, the conceptual model of most auto-"time trackers" doesn't work at all. Yes, I was hopping back and forth between a PDF viewer and a text editor all morning… what does that tell me? Storing the window titles adds little extra signal (for me). And I'm often AFK.
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I should warn folks trying this app: it has no data visualizations whatsoever; it just exports JSON, which you can then munge however you like. Not ideal, but…
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I used this app to collect the data: apps.apple.com/us/app/tracker Unfortunately, it only supports one prompt at a time. I'd also like to sample eg: - "How curious am I feeling?" - "How dutiful am I feeling?" - "What am I thinking about?" (can use scribble / watch mic / top list)
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Mr. has a very intense way to achieve self-sampling: a dedicated smartphone set up on his desk, which demands input every minute(!) about what he's doing.
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Stochastic self-sampling makes a lot more sense for me. i.e. at random periodic intervals, ask: what are you doing? This has to be extremely low-friction, of course. Unfortunately, existing solutions assume all my work is at my computer… messymatters.com/tagtime/
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Yes! Stochastic sampling is a shockingly effective method at low overhead - whether sampling code or humans. I set up a system like that on myself once - to find sources of distraction “what are u actually doing v what are u supposed to be doing?” - worked great.
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