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Authors: John Havens
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issue from above with a little tweak:
Just because a certain technology hasn’t been built doesn’t mean it shouldn’t be.
Facebook has bigger priorities than creating technology that can accurately identify if a person is genuinely under the age of thirteen. That’s not a question—if 5.6 million users might be under the age of thirteen and Facebook isn’t actively creating a technology to ban them as mandated by the Federal Trade Commission, by definition their priorities are clear. The fact they’d stand to lose 3.5 percent of their U.S. market if kids were bumped from the site also speaks to their priorities.
Parents helping underage kids to game the system are acting on their personal preferences. The fact remains, however, that parents are breaking the spirit of COPPA when they help kids under thirteen get on Facebook and that the company stands to benefit when these kids join the site. And now those kids will start getting tracked earlier, with their data being utilized or sold in ways they don’t realize.
The fact that Facebook hasn’t built a technology to accurately identify if someone is under thirteen doesn’t mean they can’t . And as they’ve created the largest pool of photographic data in the world identifiable by facial recognition technology, I think they’d be able to block kids better if they wanted. Their facial recognition technology launched as opt-out only (versus having users take the extra step to opt in), implying they don’t want users to be able to opt out because it messes with their ability to monetize.
It’s this lack of clarity around privacy that is fostering distrust from users and helping to create the personal identity management industry.
The Context of Data
Data is like your health. You don’t really appreciate the way that data is being handled until something bad happens to you. 3
—WILLIAM HOFFMAN, director of the World Economic Forum’s Information and Communications Technologies Global Agenda
Unlocking the Value of Personal Data: From Collection to Usage , 4 written by the World Economic Forum (WEF) in collaboration with the Boston Consulting Group, provides an excellent overview of the evolution of modern data collection and practices. The report was generated as a result of a series of global workshops conducted by the WEF over the course of a number of months in 2012.
One of the biggest difficulties about data collection has to do with the context of what it will be used for. For instance, in measuring health data regarding a particular disease or condition, knowing personal information about individuals in a trial will lead to greater insights than by using anonymized data. So a practice of always separating people’s identities from the results of their trials or other contexts can hinder innovation.
There is also a technical issue with anonymization that any data scientist will remind you of: As a rule, it’s often impossible to achieve. In an effort to demonstrate the need for consumer privacy, famed Carnegie Mellon researcher Latanya Sweeney showed that 87 percent of all Americans could be uniquely identified using only three bits of information: their zip code, birth date, and gender. 5
For these and other reasons, WEF’s report calls for a shift from controlling data collection to focusing on data usage. A primary reason for the shift is the evolution of Big Data, which refers to the exponentially large sets of information that need to be aggregated and studied before even knowing if they contain potential for insights. As the WEF report notes:
Often in the process of discovery, when combining data and looking for patterns and insights, possible applications are not always clear. Allowing data to be used for discovery more freely, but ensuring appropriate controls over the applications of that discovery to protect the individual, is one way of striking the balance between social and economic value creation and protection. 6
The distinction
Just because a certain technology hasn’t been built doesn’t mean it shouldn’t be.
Facebook has bigger priorities than creating technology that can accurately identify if a person is genuinely under the age of thirteen. That’s not a question—if 5.6 million users might be under the age of thirteen and Facebook isn’t actively creating a technology to ban them as mandated by the Federal Trade Commission, by definition their priorities are clear. The fact they’d stand to lose 3.5 percent of their U.S. market if kids were bumped from the site also speaks to their priorities.
Parents helping underage kids to game the system are acting on their personal preferences. The fact remains, however, that parents are breaking the spirit of COPPA when they help kids under thirteen get on Facebook and that the company stands to benefit when these kids join the site. And now those kids will start getting tracked earlier, with their data being utilized or sold in ways they don’t realize.
The fact that Facebook hasn’t built a technology to accurately identify if someone is under thirteen doesn’t mean they can’t . And as they’ve created the largest pool of photographic data in the world identifiable by facial recognition technology, I think they’d be able to block kids better if they wanted. Their facial recognition technology launched as opt-out only (versus having users take the extra step to opt in), implying they don’t want users to be able to opt out because it messes with their ability to monetize.
It’s this lack of clarity around privacy that is fostering distrust from users and helping to create the personal identity management industry.
The Context of Data
Data is like your health. You don’t really appreciate the way that data is being handled until something bad happens to you. 3
—WILLIAM HOFFMAN, director of the World Economic Forum’s Information and Communications Technologies Global Agenda
Unlocking the Value of Personal Data: From Collection to Usage , 4 written by the World Economic Forum (WEF) in collaboration with the Boston Consulting Group, provides an excellent overview of the evolution of modern data collection and practices. The report was generated as a result of a series of global workshops conducted by the WEF over the course of a number of months in 2012.
One of the biggest difficulties about data collection has to do with the context of what it will be used for. For instance, in measuring health data regarding a particular disease or condition, knowing personal information about individuals in a trial will lead to greater insights than by using anonymized data. So a practice of always separating people’s identities from the results of their trials or other contexts can hinder innovation.
There is also a technical issue with anonymization that any data scientist will remind you of: As a rule, it’s often impossible to achieve. In an effort to demonstrate the need for consumer privacy, famed Carnegie Mellon researcher Latanya Sweeney showed that 87 percent of all Americans could be uniquely identified using only three bits of information: their zip code, birth date, and gender. 5
For these and other reasons, WEF’s report calls for a shift from controlling data collection to focusing on data usage. A primary reason for the shift is the evolution of Big Data, which refers to the exponentially large sets of information that need to be aggregated and studied before even knowing if they contain potential for insights. As the WEF report notes:
Often in the process of discovery, when combining data and looking for patterns and insights, possible applications are not always clear. Allowing data to be used for discovery more freely, but ensuring appropriate controls over the applications of that discovery to protect the individual, is one way of striking the balance between social and economic value creation and protection. 6
The distinction
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