Fears About Big Data Unfounded, Report Says
Posted at 8 a.m. on May 14, 2014
A report from the Technology Policy Institute says there’s no evidence that big data harms privacy. “Privacy advocates, scholars and public officials have raised concern over a number of potential privacy threats from big data,” the think tank’s report says. “As of now there is no evidence that any of these threats has materialized.”
For example, the report looks at Privacy Rights Clearinghouse and Identity Theft Resource Center numbers on data breaches and says that together, they suggest the trend has slightly risen since 2005, but when deflated by the amount of online commerce, data breach risk has been relatively constant.
When looking at the number of records compromised, the trend since 2005 is “relatively constant or even declining slightly,” the report says. And when deflated by the amount of online commerce, the trend declines somewhat more, according to the report by TPI, which is backed by various tech and telecom companies.
And while there are concerns about the potential use of big data to make decisions like whether to hire someone, the report argues that it’s already happening on a smaller scale:
The Federal Government, including the FTC, uses class rank in hiring lawyers. These decisions are based on “small data” — sometimes, one test score or one data point. Big data can only improve this process. If more data points are used in making decisions, then it is less likely that any single data point will be determinative, and more likely that a correct decision will be reached.
The report goes on to call as “non-examples” the examples in a White House report on big data released this month that were used to illustrate a finding that big data could result in discrimination.
It concludes that approaches to privacy that limit data sharing would be harmful:
Using data in unanticipated ways has been a hallmark of the big data revolution. The standard solutions that would limit the reuse or sharing of data would be particularly harmful if applied to big data because they are inconsistent with the innovative ways in which data are being used. This would have a detrimental impact on innovation in a variety of sectors, from marketing to credit markets to health research.