Privacy Essential to Big Data Projects

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By George R. Lynch

May 12 — Big data has a huge upside for companies if they apply best practices and ethical considerations to their business model, according to privacy attorneys at the annual International Association of Privacy Professionals conference in Toronto.

Attorneys must raise ethical, fairness and public relations issues with companies that decide to utilize big data, Melissa Krasnow, partner at Dorsey & Whitney LLP said during a panel discussion.

The panel was moderated by Barbara Yuill, news director for intellectual property; tech; privacy and data security; and telecom at Bloomberg BNA.

Companies must have a basis to justify how big data projects have been designed and carried out, she added, including justification of the analytics algorithm.

If companies take certain steps to ensure that data privacy is preserved, then the “privacy will give you a competitive advantage because it will benefit you from a business perspective,” Ann Cavoukian, former privacy and information commissioner of Ontario, Canada said.

One of the best ways to take advantage of big data is to design big data projects and technologies with privacy tools at the outset, Cavoukian and Krasnow said.

Treating privacy as a business issue will have a positive impact on the bottom line, Cavoukian said. If companies incorporate privacy into their business model, instead of looking at privacy protection as a nuisance, then customers will show their appreciation with their loyalty, she added.

Steps to Be Taken

Big data projects should always be discussed with interdisciplinary groups before they are implemented, Krasnow stressed. Interdisciplinary groups may include statisticians and data scientists that can spot possible security and discriminatory issues in the method before projects are implemented.

The importance of designing data systems to remove bias was recently highlighted, Krasnow pointed out, in a White House report that introduced the term “equal opportunity by design,” a play on Cavoukian’s privacy by design concept of putting in place safeguards at the engineering stage.

De-identification of data could be one way to protect individual privacy in big data projects. Data that is de-identified presents as low as a 0.01 percent chance of being re-identified, Cavoukian said, making it an acceptable risk in light of the potential upside that big data represents.

The problem with de-identification, however, is that there is relatively little known about the science of de-identification after more than a decade of research, according to studies. So the question becomes, Krasnow said, how much risk are companies willing to take.

But the bottom line from the panel was that privacy will enhance big data’s potential if attorneys and companies work together to address the privacy issues inherent in big data analytics. “Privacy isn’t an impediment that stifles innovation,” Cavoukian said. “It breeds innovation.”

To contact the reporter on this story: George R. Lynch in Washington at

To contact the editor responsible for this story: Jimmy H. Koo at

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