What does work is identifying cases where there is genuine cause for concern - symptoms for healthcare patients, lack of ability to complete tasks for procrastinators - and collecting the data needed to determine if/when intervention is required.
The challenge for the quantified-selfers will be to sort the signal from the noise.
It's a basic fact of life that you make better decisions with more information available, presuming you can think about that information sanely.
Humans generate lots of information, and computers can capture and record that information. It seems like there has to be some intersection, where we can write programs that help us make decisions.
That's not totally there yet, but it doesn't make monitoring bad. The worst case is that the data isn't useful right now.
* collecting data * having clean data * extracting the right indicators and analytics from the data
I think the problems remain the sames with QS. Actual QS solutions lack of interoperability, do not really allow experimentations and do wrong about privacy. That's why Cozy could help: it allows to build data collectors in a few hours, a data browser is available to clean wrong data, and the best of all it allows anyone to hack new stuff on top of this new set of data without compromising privacy.
disclaimer: Cozy member
