About four years ago, an irate father in Minneapolis walked into his local Target shop with a complaint. He wanted to know why they were sending his daughter, who was still at school, vouchers for baby clothes and cots. Were they trying to encourage her to get pregnant?
When they telephoned to apologise a few days later he was more diffident. His daughter had fessed up: a child was due in a few months. But if dad hadn’t spotted any telltale signs of pregnancy, the shop had: she’d been rumbled by her recent purchases, in particular unscented lotions and certain dietary supplements. Some algorithm had spotted the significance of a sudden change in her buying habits, and triggered the ‘bombard with new‑baby offers’ subroutine.
But if you think that’s worrying…
A friend had been buying a few outdoor items on Amazon, and these three recommendations appeared. Should he expect sudden murderous urges? A visit from the police? Even if the prediction was wrong in his case, it seemed to suggest there were rather more psychopaths and kidnappers in Britain than previously suspected (and also that, as a group, they were inclined to be frugal when buying balaclavas and rope but knew not to skimp when it came to choosing a good duct tape — a handy lesson there for Spectator readers).
Fortunately, there is a more innocent explanation. The incident happened at the height of the paintballing craze and, as someone subsequently explained, all three items are regularly bought by serious paintball aficionados, or by the people who run paintball centres. Phew!
Like it or not, we generate an enormous amount of data as a consequence of our daily actions. This is worrying when it’s our data but, let’s be honest, irresistibly intriguing when it’s everyone else’s: what people do online is just so much more revealing than what they say in public.
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