Somebody Like You
At the last Facebook Developer’s Garage we attended, a gentleman was introducing a new app for tourists and travellers, one that introduces you to restaurants and sites you may like, recommended to you by people like you. It is hard to imagine that the Facebook “like” button was introduced just over a year ago, when it seems it’s always been the way we’ve shared our digital preferences. Listening to this presentation (and numerous similar ones over the last months), I couldn’t help but feel a little unnerved that app developers are equating similarity and familiarity to good and, inevitably, the unknown and different to bad. Has nobody stopped to wonder where this may lead us?
At our recent presentation on the future of design at Brunel University, we explored the evolution of empathy, which starts with the finding that humans are neurologically soft-wired to be empathetic to one another and explains how through evolution we’re continually expanding our circle of empathy (from early tribalism and blood ties, to religious ties, to the fiction of the nation state, etc). The theory went on to ask whether technology could possibly be the next thing through which we learn to broaden our sphere of empathy to a global one. I’m a fan of this concept and see many examples of how technology is helping us evolve in a positive way, for instance, in IT4DC (Internet Technology for developing countries).
To me, this seems harshly at odds with us liking and therefore moving closer to things, places and people that are “like us”. Surely recommendations based on what I’ve previously experienced and enjoyed will eventually narrow my horizon, steering me towards the known and away from the unknown. On social networks such as Twitter and Facebook I am quite obviously surrounded by people that I know, like and share certain views with. The more time we spend online, the more the Internet becomes like us – your personal online window onto the world, reflecting your experiences, likes and dislikes.
How about an algorhythm that on every tenth recommendation suggests something that you are unlikely to do or to like according to your previous data? As in a “try something new” or “broaden your horizon” app, instead of “You have previously purchased a book on gardening, here are 10 other gardening book you might enjoy!”