Tim Whitlock, chief technology officer and co-founder, Brandfeed
Most people understand that sites like Facebook are free to use for a reason. It’s not because Mark Zuckerberg loves you, it’s because Facebook and its peers make money from your data and from your eyeballs. At least I hope people understand that. At the very least I hope that people understand they’re making a trade of some sort and that they’re ultimately in control of this arrangement.
Whether this is optimistic or not, if we want to maintain any kind of control over this trade, we need to start thinking beyond what our data is currently used for. We need to start thinking beyond targeted advertising, and wonder what else the information we hand over today might be used for tomorrow.
Suppose Facebook knows you drink too much. Suppose one day that affects your life insurance premium, or your eligibility for a new liver.
Maybe you think I’m crazy, but consider a couple of well-established markets that might do well to get their hands on the kind of data that Facebook has.
Last year, Deloitte Consulting conducted an experiment for Aviva insurance. It used marketing data from Equifax in place of traditional insurance application data. What amounted to lifestyle information, such as hobbies and favourite TV shows, was used as part of a predictive model in assessing applicants for life insurance. Aviva found the results “persuasive”.
Credit information company Experian bought a majority stake in social media marketing agency Techlightenment earlier this year. If you can’t buy Facebook, perhaps the next best thing is to buy a company that makes products on its platform. It’s certainly one way to investigate how social media data might fit into your traditional business.
Beyond your basic profile, every status update or tweet potentially contains intricate behavioural and lifestyle data; it’s just that nobody can make much sense of it at the moment.
There are countless startups concerned with “making sense of the noise”. Whether it’s to extract brand buzz, make stock predictions or match people to interesting peers, the goal is fundamentally the same – to turn this vast, organic stockpile of chatter into something discernible and, therefore, valuable.
Our current ability to do this is questionable, but firms are investing in the problem. The speed at which Fflick was acquired by Google was pretty staggering. I’m going to guess it wanted the Machine Learning PhDs rather more than its database of movie reviews. In five years time, who knows what engineering problems will have been cracked? Who knows what insights may be gleaned from a decade of Facebook wall posts?
With all of this data, the right technology and a pretty good idea as to your real identity, it seems that today’s big social networks are well suited to becoming tomorrow’s data analysis and profiling companies. The likes of Experian and Equifax must be somewhat concerned, but we should keep our eyes open too, because this is our data.
The law, at best, protects us from the world as it is today. It struggles to keep up with technology as it is. So I wonder, will the data we pour onto the internet today be protected by the laws of tomorrow? Hard to say when we don’t know what technology will exist, or what the big players will decide to do with it.