Social media and technology researcher Danah Boyd likes to tell this story as an illustration of the power of mass data gathering:
A couple of years ago, a 16-year-old Minneapolis girl received a mailing advertisement from Target. The ad congratulated her on her pregnancy and suggested she buy some infant care products.
The girl’s father was incensed and chewed out the manager of a local Target store. A few days later, the father called the manager to apologize—his daughter was pregnant, and Target’s corporate marketers and statisticians had found out first. They had learned to predict—based on consumer buying habits—when shoppers were expecting children and the girl’s recent purchases had raised a red flag.
What Target failed to do, Boyd told an audience at the University of Virginia on Friday, was to understand the implications of using the data.
“What’s happening is an analytic correlation … without information for what that correlation will do as it’s shared with other people,” said Boyd (who changed her first and last names legally to be lowercase).
The author and researcher was the keynote speaker at the first National Conference on Big Data Ethics, Law and Policy at UVA. The university recently started a Data Science Institute, and one area the institute hopes to tackle is the ethical and legal implications of mass data collection.