Big Data Ethics: 4 Principles

A proposal to crowdsource a set of big data privacy guidelines, starting with transparency, simplicity by design, and security.

PrivacyMark van Rijmenam writes in Smart Data Collective, Mar 13, 2013 Big Data Ethics: 4 Principles to Follow.

He notes that we now get a lot of the software or apps for free, but the price for that freedom is our data. Google can provide you so many free services because it uses your data to show you targeted advertising. Facebook shows you personalized tailor-made advertising based on all your data to pay for the software and make money.

It may take too long (is never too long?) to wait for various governments to come up with a global set of privacy and ethical big data guidelines. In the meantime the public will have to learn the limits and understand how much privacy we want to keep and how much to give up in exchange for free stuff.

It might be easier to 'crowd-source' a set of big data privacy guidelines.

He proposes 4 principles:

  • Radical transparency: Tell your customers in real-time what sort of data you are collecting and for what you will use it.
  • Simplicity by design: Users should be able to simply adjust any privacy setting and they should be able to determine what they want to share or not. Facebook is a good negative example: their privacy policy contains more words (5,830) than the US Constitution (4,543, without amendments).
  • Preparation and security are key: Define what information and data you really need to do business and what information you can do without.
  • Make privacy part of the DNA: When you embrace transparency, simplicity and security, your customers will embrace you.

What do you think?

Read more.

See also Ethics of Big Data: Balancing Risk and Innovation, by Kord Davis.

See also KDnuggets Poll: Should there be a Data Scientist Pledge?