A common concern with big data is privacy – where do we draw the boundary between public information that can be mined, and private information that cannot. This becomes increasingly acute as people are broadcasting more information about themselves.
Existing data protection laws generally allow individuals to request that the data stored on them be deleted. These laws, however, become less effective once we move beyond explicitly-entered personal information, for the following reasons:
1. We don’t know when we’re being tracked
There is no simple way to find out when and what data is being collected. Furthermore, suppose data collected is passed on to another party with a requirement to delete that data within a certain time period, there is no way of telling if that requirement has been honored. Ownership cannot be enforced if we don’t know what data is being held.
2. We don’t know the source and provenance of data
Data collected is generally passed on to other parties without tagging the recipients in between. Hence there is no way to tell if data collected comes from a Google search, a photo posted on Facebook, a purchase on Amazon, or a tweet on Twitter, as well as future intermediaries. Ownership cannot be enforced if we don’t know where it came from.
3. We don’t care
While there is a lot of concern on adverse effects of technology on privacy, most people are not bothered unless it’s causing them problems. Most of the time it doesn’t. Property law works because they enforce an intuitive feeling of ownership. “If nobody cares about ownership of their data, we’ll never pass or enforce legislation around the concept.”
Read the full article here.
This week, we feature the best articles on limitations of Big Data. In particular, Tim Harford makes an excellent case on why correlation does not equal causation.
Image credit: Flickr
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