next they will want to track who you meet with, how much time you spend with them
Who you meet with, and to some extent how long you spend with them, can be derived from analysing the tracking data of individuals e.g. knowing that three separate people are in the same coffeeshop together on several separate occasions at different times leads to the conclusion that they're likely to know each other.
This is the pernicious thing about tracking people; data about individuals builds to become information about groups.
True. The power of tracking through big data analysis can be really really dangerous. Having a burner cellphone (B) one never used to call anyone (C) is useless if it's always carried around with the main one (A) so that it always updates through the same Wifi connections and links to the same cell towers at the same time. A and C's are already related, so a quick analysis will relate also A and B, then B with C's although B and C's never called each other and don't share their respective numbers in their phonebooks.
>" knowing that three separate people are in the same coffeeshop together on several separate occasions at different times leads to the conclusion that they're likely to know each other."
Does it? Three people who visit the same coffeeshop at the same time in the morning also leads to the conclusion that they all live on the same block and work 9 to 5 jobs.
You missed two points. Firstly "at different times" meaning people who are all there at 3pm one day, 10am a different day, and 4:30pm on another day. That's a strong indicator that they're not there coincidently if they don't appear there at other times as well. Secondly you missed where I said "likely to know each other". Mining large data sets for relationships is all about probability, as nothing is really guaranteed to be 100% certain, but you can get to quite high confidence levels with relatively small amounts of data.
Lots of data at hand means also one can more easily filter out false positives. 3 people in the same coffee shop can be totally strangers to each other, but if their phones start connecting to the same towers in different places all far away the coffee shop at the same times, one could conclude they're likely related someway.
So you're saying the inferred information doesn't exist because of some false positives? I'd say false positives can be more dangerous because humans will have propensity to trust the algorithm and interpret it as truth
>Recently India has started tracking its citizens with their fingerprints, every thing they buy, every place they visit, every money transaction, everything.
Can't you just use cash? I assume my credit card company, my bank, their partners, and the government know where I am if I use the card. Isn't that the logic thing to think?
The US is very cash centric, but a lot of countries are slowly migrating away from it. Many stores don't accept cash and it is mostly the older generation that continue to use it.
If we want cash to remain stores must be forced (by law) to accept it, and this must be done soon. Even if we go that route you will quickly become that weirdo that payed in cash if you actually makes use of it.
Who you meet with, and to some extent how long you spend with them, can be derived from analysing the tracking data of individuals e.g. knowing that three separate people are in the same coffeeshop together on several separate occasions at different times leads to the conclusion that they're likely to know each other.
This is the pernicious thing about tracking people; data about individuals builds to become information about groups.