smile / frown
After a long-drawn-out draught in the personal coaching software space, two promising contestants entered the market a while ago. Lift is offering “a coach that goes everywhere with you,” Everest strives to help “live your dreams and achieve personal goals.”
It’s obvious that – at least until we’ve reached singularity – services like these two1 cannot replace interpersonal consulting, but they can help people achieve intrapersonal change: List the behaviors you’d like to change, and start shaping your behavior; it’s as easy as that.
What’s missing in the equation are two things – one which is well-known and one that is new (to me). What’s well known is that it is rather difficult, if not impossible, to always assess one’s own behavior in a way that is beneficial for the system as a whole. If your goal is to become a bigger asshole, that may be fine with you, but the rest of the system (colleagues, family) may object. That’s the reason why external consultants or counselors are so important at least in the phase in which you’re finding out which behaviors, skills, or values you’re going to shape.
The second missing link is that algorithm-(app-)driven behavioral change (what the young’uns may call “mind hacking”) is missing an external feedback device that can either evaluate or at least measure if and when a habit is changing, or has changed. There are a multitude of facilities for, as they say, quantifying yourself, but all of them stop short at measuring what’s happening in your body: Of course, pulse rate may be an indicator of stress, and your number of daily steps is an indicator of for how long you’re not slumping in your chair, but there are many signals that a human counselor can easily discern which computers are just starting to learn about. I’ve been working in this field for nearly 15 years now, and I’ve learned to gauge a client’s blinking rate, breath position, eye movements, etc., to get an idea of what’s happening in his mind right now.
So … what to do when putting probes into our brains at the office is (still) unpractical and we’d like feedback about mental processes to help a user optimize intrapersonal behavioral change? There has been some research in facial feature detection, and the algorithms are quite robust. So someone might use a (say) MacBook’s internal camera to count the seconds per day its user is smiling and contrasts this measurement with the seconds per day he’s not. Maybe add some contextual information: Smiles per second when reading e-mail, frowns per millisecond when debugging code. This won’t give exact measurements (unless we’re going to use a multi-camera setup), and of course, smiling does not necessarily equal to “feeling well,” and I’m sensing some people getting aggravated because of privacy issues, but still.
Who goes first?