The problem with big data is that they need interpretation, argued sociologist Tricia Wang on the recent EPIC2013 in London. In the way they seem like the oracles in Ancient Greek. More numbers does not mean we are better in predicting the future. A report by Erin Taylor.
The big problem with “big” data, claims Wang, is that we feel that it reflects truth, yet it really requires interpretation. And we can get our interpretations incredibly wrong. She presents the case of an American family who were visited by an anti-terrorism force after the Boston bombing. The woman had googled “pressure cooker” and her husband searched for “backpack.”
It’s not just the government who can’t see the context forest for the data trees. Wang reports that Kodak filed for bankruptcy despite being early players in the digital camera market. The problem was that they assumed that customers would use digital cameras in exactly the same way as analog cameras. But sharing and printing practice changed completely as cameras were integrated into a polymedia landscape.
Wang uses these divergent cases to argue that ethnography gives data context: all numbers need interpretation and analysis.
Curiously, some parties are trying to quantify the qualifiers. Apparently, Unilever now require all ethnographers who work with them to be accredited by Unilever themselves. They’ve invented a host of metrics to determine what counts as good ethnography. It’s nothing if not ironic that they are using quantification to judge a method that is being used to solve problems that quantification can’t handle.
The full report by Erin Taylor.
Tricia Wang is a speaker at the China Speakers Bureau. Do you need her at your meeting or conference? Do get in touch or fill in our speakers’ request form.
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