@tripu I have some issues with measuring and quantifying everything.
In theory, having lots of data sounds nice. But in practice, some problems tend to come up:
Data quality. Even if you do your best, collecting all possible data would stop you from excluding data with questionable accuracy. If you add a score for “quality”, the meaning of that would evolve, and the task would become recursive without an end condition.
Chilling effects. If you collect data that might possibly be deanonymized (or is personal from the start), people will experience anxiety over what you do with this data. Even if you are trusted, any data collected can become public with security breaches. I would equate unbridled data collection to inflicting suffering.
Extra problem: deanonymization. If you collect more and more data, surprising ways to deanonymize data can come up.
Overwhelming amounts of data. If you have more data than you can even roughly comprehend, how would you process it? Machine learning demonstrates this from time to time by coming up with surprising results. But since we have no idea how those results were achieved, they are worthless. Could be a mistake, a correlation and not a causation… without comprehension knowledge is meaningless. I think of this in terms of the distinction between intelligence and wisdom.
If you meant that we should strive to collect data that is meaningful to solve specific problems i totally agree. Thoughts?