In poker, they call them tells. The little physical signs that we can’t control that give away our inner mental state. What happens if we make these privately machine-readable?
For me, a lot of the fun of future technologies isn’t new tech per se, but the coming together of three or four older things, refined by new physical capabilities and design understandings, to push over the Hill of Single Use into a new valley of possible products. A strained metaphor, perhaps, so let me give you an example. Heart rate monitors have been around for years. I’ve been running with one strapped to my chest for at least a decade myself, and in those days the data has been restricted to its one single device (and later to a single app, barring the export of averages and such very high-level takes). You certainly didn’t wear an HR monitor all the time, and even if you did, you couldn’t use what it saw for anything other than athletic training.
The Apple Watch has an HR monitor on its back, has local processing, a data connection (and through that, infinite cloud processing) – but more than that, it has access to everything else we might do digitally, Not just publishing capability (send my HR to Facebook, Tweet when I go over 180, and so on) but a form of sense-making too. The complex network around the Apple Watch knows an awful lot about your personal context – that’s really its point after all – and so it could start to make all sorts of correlations between HR and that context.
We know that changes in HR can reflect changes in psychological state. Your heart beats faster when you’re aroused or stressed or angry. And we now have a device that can notice that tell, and try to work out what is causing it. What might that do? Here are some scenarios, and possible products:
- One to One. You regularly meet with someone, Mr X, who drives you insane. A deeply stressful person, who causes your heart to beat hard as you restrain yourself from violence. An asshole of the highest order. Your system detects the increase in heart rate, and sees it happens whenever you have a calendar appointment with Mr X. Matching the appointment data with LinkedIN, it identifies Mr X, and posts the “Meeting with Mr X is stressful” posit to a LinkedIN API-using offshoot, a “Rate My Meeting” clone. Over time, Mr X’s rating is further added to by others’ systems, perhaps without user input at all, flagging Mr X as (algorithmically designated) asshole. The system acts accordingly.
- Many to One. You walk to work down Oxford Street, but prefer to slip through side streets if the foot traffic is annoyingly dense. Luckily, the HR monitors on the wrists of tens of Apple Watch wearers already on Oxford Street are spiking higher than they usually average here, at this time of day, with this sort of weather. Your system notices this, and gently nudges you away from the area, pre-emptively avoiding the stress that others are giving away to the network.
- Many to Many. You’re at a concert, and having a splendid time. Your HR is rising as the music builds, and from your watch you can see that others in the crowd are feeling it too. The crowd average HR goes past 140…141…144….147…….149……and as soon as it reaches 150, it triggers the drop, the stage pyros, the lasers, the dancing girls. The musicians onstage, able to reach their musical climax just as the audience reaches theirs. That’s showbusiness.
None of these use-cases, and there are many more, require a new magical technology. Apart from the actual heart-monitoring, you could prototype them today all quite (handwaving here) easily. But none of them would work without a good installed base of constantly available HR monitors already in place. That, if Apple and Jawbone and the rest get their way, is what we’re about to have. It’s a whole new product/service category, being unlocked almost by mistake.