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CIOs should push big data projects but prioritise privacy

Thor Olavsrud | June 3, 2014
In its recent report on big data and privacy, the White House again pushed for a Consumer Privacy Bill of Rights that could adversely affect some big data initiatives. Experts say CIOs should continue to push their organisations to leverage big data analytics, but they must also make consumer privacy a priority.

Based on the Fair Information Privacy Principles (FIPPs) that formed the core of the Privacy Act of 1974, the Consumer Privacy Bill of Rights is a call for "government-convened multi-stakeholder processes to apply those principles in particular business contexts; support for effective enforcement of privacy rights, including the enactment of baseline consumer privacy legislation; and a commitment to international privacy regimes that support the flow of data across borders."

Specifically, the rights include the following:

  • Individual control. Consumers have a right to exercise control over what personal data organizations collect from them and how they use it.
  • Transparency. Consumers have a right to easily understandable information about privacy and security practices.
  • Respect for Context. Consumers have a right to expect that organizations will collect, use and disclose personal data in ways that are consistent with the context in which consumers provide the data.
  • Security. Consumers have a right to secure and responsible handling of personal data.
  • Access and Accuracy. Consumers have a right to access and correct personal data in usable formats, in a manner that is appropriate to the sensitivity of the data and the risk of adverse consequences to consumers if the data are inaccurate.

Consumer Privacy Bill of Rights Could Harm Big Data Discovery
While those proposed rights may seem sensible and innocuous on the face of it, Daniel Castro, director of the Center for Data Innovation at nonpartisan think tank The Information Technology & Innovation Foundation, says they have the potential to kill a large part of the promise of big data analytics.

"It's based on FIPPs, which was designed in the '70s," Castro says. "The reason that matters is that FIPPs was designed with the understanding that all innovation occurs before you collect the data. You figured out what you needed and then went out and collected the data. Big data is very different. All innovation occurs after you collect the data. FIPPs would say you have to know how you're going to use the data before you collect it, and then you only collect the data that you're going to use. It doesn't allow companies to have that experimental approach to data."

Much of the promise of current and emerging big data analytics technologies is the capability to perform discovery on massive and varied data sets to generate new insights. This process is not as much about learning the answers to questions as it is about determining which questions you should be asking in the first place.

Castro argues that if the government limits organizations to only collecting data for a purpose specified at the outset, and only using that data for the specified purpose, a great deal of the power of big data will be lost. Additionally, he says, American organizations will find themselves at a competitive disadvantage against international organizations that are not limited in such a way.


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