This is an application of ActivityWatch data I’ve had for a while but haven’t gotten around to writing down. The idea is twofold:
- Help the user adopt certain behaviors
- Such as browsing Facebook/Reddit less
- One approach is a kind of “focus time” when distractions are blocked (or the user is incentivized to not be lured in by).
- This is already done by StayFocusd and can also be done with RescueTime Premium (I think).
- Predict and prevent unwanted mental states (such as depression and anxiety)
- It’s been known that Facebook can predict when you are going to break up with a partner, or if you are depressed.
The first thing is a lot easier, but the second thing is (to my knowledge) largely unexplored territory (have been speculated about, but haven’t been done).
There is no doubt much value in being able to predict if a person is going down a bad spiral into depression (Scott Alexander has written about this). A large part of the problem has always been how to predict these things with the limited data available when you care about ethics and privacy. That’s where the self-ownership of ActivityWatch data could change things.
The remaining challenge is how to train the predictive model (both how to deal with privacy and how to make it good at predicting something as complex as depression). I hope the research and user community could come together on the data privacy part (some self sacrifice of privacy might be pragmatic).
Let me know what all of you think about this. These forums are pretty dead right now so I don’t expect a reply anytime soon but I’ll link to the thread and update it when progress is made.