Who is watching the watcher?

Don’t you just love being ‘connected’ and all the possibilities you have via the internet, I am sure you won’t want to go back the dark ages without your PC or your smartphone.

Still, there is a dark side to this connectedness. One I have mentioned a few times [http://kapiti.seniornet.co.nz/2015/12/03/data-data-data/] and that is the collecting of your private information, not just names and email addresses, but what you are doing on the internet, the websites you visit and what you are up to on those sites, from porn to facebook. But then you knew that already.

What you may not have considered is how Big Data can explore such information and not just commercially, but even criminally. How you might feel if a hacker threatened to let all your contacts on e.g. facebook know which websites you visited. Did you know that Banks overseas, and most likely here in NZ too [unconfirmed], are preparing to offer services tailormade to your needs?.

How?, you say, well they use data analysis – big data – where they assemble enormous amounts of publicly available information about their customers’ behaviour and doings. Facebook page content, information about income, where and how they live, whether they own their house, car etc. plus the bank’s own internal data are all cross referenced until the bank is ready to market their products to their customers.

Imagine this highly unlikely scenario: you receive an email from your bank saying: ‘Our computer tells us that you have fallen in love with your lover and that you and your wife is getting a divorce. Do you need a loan for a new property deal?’ Here the borderline for privacy would no doubt have been crossed, but the future tells us that the banks will have available that kind of information purely based on the digital tracks we leave to allow them to interact with customers in a more precise way.

I came across a report last year from a biggish bank based on data from 100 households giving the ages of the neighbours, number of children at home, how the neighbours voted, their occupations, income, any criminal convictions, and level of education. It was to be further expanded to include the schools nearby and their exam pass marks, traffic noise and quality of the potable watersupply. They felt it would all be helpful to get closer to their customers especially the half of that area’s inhabitants they did not already do business with.

You can also see that low income earners could easily be excluded from credit or loans, and it is easy to profile people based on income, address and activities and decide who is the bad risk. So they are excluded from a credit evaluation because of the collected computer data, and it may be quite unfair.

It is of course little different from what the other Big Data collector do, Google aims its advertising on your buying habits. If you just bought a new dress over the net you will likely see a prominence of adverts for apparel, handbags, shoes etc following shortly after.

The enormous amount of data – imagine if all of it was burnt to CDs and they were stacked on top of each other, then they would reach to the moon and back, not once but three times. Clearly the opportunities hidden in this mass of data is massive too, and just think that every minute there are 695000 status updates on Facebook alone, add the 100000 tweets, the staggering millions of SMS, the 168 million sent emails, plus all the data transmitted.

I don’t know if governments will try to regulate or if they really comprehend the monster that could grow from unethical use of such information. Then again perhaps we don’t care enough about the protection of our privacy, but as they say ‘watch this space’.