People think I’m crazy for deleting my Facebook wall each day. When I’m put on the spot about this (usually after a few beers) I tend to rattle on like a deranged conspiracy theorist and generally make it much worse for myself.
One comment usually brings the issue home quite nicely though. I ask:
“How often to you mention being drunk, or being hungover on your Facebook wall?”
– the answer is invariably “often”
“What if in five years you can’t get life insurance because you’ve been profiled as a high risk for alcohol-related illness?”
Should I be paranoid?
Long version coming up
I got a Debenhams store card the other week. I was asked the usual credit-check questions, but after the first dozen I got suspicious. I asked the lady if these questions were ‘optional’; she confirmed that they were, so I opted out.
We’ve become more-or-less comfortable with the concept of credit checks – they’re a necessity of our financial lives. But these optional questions were pushing the boundary a bit, they seemed like more general demographic profiling questions. I suspect that my card was approved as soon as they had my name and address.
Most people are aware (I hope) of how our purchasing habits (through things like Nectar) can be used to build up a profile of us as consumers. It all seems pretty harmless when you get a voucher for tiramisu through your door, but what if marketing data affected more important things in your life than free cake?
A recent article in Wired led me to an experiment by Deloitte Consulting. The experiment was a predictive modelling approach to the usual methods of Aviva’s life insurance underwriting. 37% of the model’s predictive ability came from consumer-marketing data. Think about that for a moment — not just facts in your medical history, but what you like to do at weekends. What we’re talking about here is extrapolation of the probability of your death.
Not only does this concept scare the crap out of me, but I immediately think about all the data I’ve pumped into Facebook and Twitter over the years. Extracting value from this kind of noisy data is clearly a hot area for startups too. Some firms (like Google-acquired Fflick) are using machine learning to turn status updates into discernible data. Once this technology is more reliable, the face of consumer profiling will take a serious leap.
The direct marketing division of Equifax was acquired last year by Alliance Data Systems for $117 million. (that’s 0.2% of Facebook’s valuation). We already know the value Facebook can bring to targeted advertising. Just imagine if Facebook entered the profiling market at this level. The ubiquitous Like button even gives Facebook the potential ability to know what other sites you visit. You may not even need to tell them you prefer the FT to the Daily Mail – they may already know.
An obvious caveat to Facebook’s profiling ability is that your Facebook isn’t necessarily tied directly to your legal identity, or exact postal address. I am merely “Tim W” and they don’t have my mobile number. However, I imagine I’m in the minority here – Facebook are very aggressive in farming this data. They even use an irritating Captcha to coerce you into ‘verifying’ your account.
How long before you can enter a person’s name and address into a system and get back a quantified likelihood of that person crashing a car, getting arrested, dying of liver failure, or skiing off a cliff?