To listen in to those conversations, and subsequently to see fragments of them pop up in an enormous grid of numbers, is a bit like witnessing people being fed into the Large Hadron Collider: lives churned and turned into statistics, a great big crunching and mashing (to use a favorite word of data analysts), a sort of digital dismemberment. You half-expect to hear screams, see a pool cue fly out and some veg on a tea towel, and the specter of a dead person on a toilet.
What is this great collider creating? What is the output of these weeks of combing streets and dialing numbers in search of cooperative people, and the subsequent weeks of chopping and reading the information they give?
The analysts have a printout showing employment.
“It’s going to add a dot here,” Chandler said.
He points to a space beyond the last little sphere in the sequence. This is where the new speck will go, small as a particle, vast as a miniaturized planet. The dot will be cut in myriad ways and replotted, scattering new solar systems across countless graphs.
“It sounds a bit creepy. A bit Orwellian, when you put it like that,” Sturgis said. “But of course these are anonymous answers. We are not interested in individual cases. What we are doing is making a map.”
Is it a double-edged comfort, that for all we are being surveyed, the surveyors are interested in only the type of individual?
On one hand “You can hide behind typologies. There is safety in that new sort of anonymity, which is no longer anonymity, but opaqueness behind proxies which pick you up well enough, but which do not really identify you as unique,” Floridi said.
There is danger in this kind of anonymity too.
“Next thing you know, because you are treating everyone as a kind of person, it becomes part of our culture. I fear that it might be changing our social interaction. And that would be sad,” he said.
If Floridi is correct, people will be kinds of people — figures — not only in public, on social media or in the files of administrative data, but in private encounters too and, perhaps, even in their own estimations.
Data collection has many useful purposes — it is not hard to see all those digits as the building blocks of our society — but it is also, to some degree, an exercise in collective vanity. As a public, we enjoy looking in the mirror that is held up to us. As individuals, we like to spot ourselves in the picture, find ourselves on a distribution line: are you more or less happy than the national average of 7.4 out of 10?
All these charts, tables and graphs are society’s selfies, snapshots taken from so many angles. Clearly we can not get enough of them; they are infinitely fascinating, and may help us to know our world better than ever before — so long as we do not lose ourselves looking.