Privacy, data, and the new Sociometrics

As always, Technology Review provides a great glimpse at the innovations coming down the pike. In this case, by innovation, I mean the continued ascendancy of sociological insight wrapped up in physics, taken up by engineering, and brought forward as the ‘next big thing’: you can actually identify people’s social networking in real-time and help them to, for example, work a crowd better; or find a more suitable financial broker; or see which institutional representatives interact with whom at an academic conference.

All else aside, I think we are approaching a new era of privacy issues, related to data mining and what counts as anonymity, what counts as data, who owns it, and who profits from it. The sociometrics model only works when we have things like smart-badges, ambient microphones, and unobtrusive surveillance. Alex Pentland, one of the MIT researchers (rightly) sees quite benign benefits from these technologies, including making non-face-to-face interactions more effective and efficient.

Transcripted from Alex Pentland’s website (.wmv movie link):

We can really measure exactly when you nod your head, and exactly the inflection of your voice, and exactly where you look, and all those things that you sort of know are important, it’s the social language. You can have a microphone that aims at different people and has a little bit of processing in there. We don’t listen to anything that violates privacy, we’re just looking at features of language. And that’s not particularly worrying to people because the words are never recorded, the meaning is never recorded. It’s really just social signals. ‘You were being pretty pushy there’. Or ‘You weren’t really being very forward there’. And we can combine that with measurements of performance to ask, how is it that your social presence affects your performance? Your working with other groups? And if we can do that, the evidence from the literature is that we can improve the working of groups, the functioning of organizations, by a lot. Not just 1 or 2 percent, but 20 or 30 or 40 percent. And of course, those are the things that drive profitability, that drive performance.

And it is indeed true that they are not recording words, or meaning, just social signals. But in an era where phone companies are data mining all voice and data activity, and financial firms are looking at aggregated transactions in the search for suspicious transactions (.pdf link), I would suggest that ‘just social signals’ are no longer a free resource. At minimum, we need a new language to capture what we used to, but no longer mean by anonymous.

And I’m not against what Pentland et al are up to, not by a long shot. I just think there are some issues that come into play that we’ve only begun to think about practically, and that we’ve not at all come to terms with theoretically or in the underlying social scientific research.

Comments are disabled for this post