Last night Susan and I watched “Catfish,” a movie from last year about a case of a fabricated online identity. The movie starts with a young man who is engaged in an online correspondence with what he believes to be a young girl who appears to be a painting prodigy. He also chats with the girl’s mother and carries on several increasingly steamy exchanges with her older sister. [Spoiler Alert!] Eventually, a variety of inconsistencies surface and he becomes suspicious. Together with his brother, who is documenting everything, and another friend they go on a roadtrip to find the family. It turns out that all of his correspondence is with a middle aged woman who has manufactured the other characters including a variety of online friends for them. She does have a young daughter but the paintings are all hers.
The movie is in the style of a documentary and there is some considerable debate online about whether or not it is an actual documentary or just a complete fabrication. The possibility that it is fabricated of course neatly parallels the plot line of the movie itself (something that seems lost on most people commenting about this online). We live in a digital age where it is not safe to assume that anything is what it purports to be. There is no certainty only different probabilities.
This has important implications for identity. We have to embrace a probabilistic identity online. On one extreme are people we interact with in person every day which is as close to “known” identity as we can get. On the other are anonymous comments on blogs. Everything in-between is a continuum. Just because someone has pictures of “themselves” and friends online doesn’t mean they are who they claim to be. Aside from Catfish, the recent exposure of two lesbian female online personas as fictitious and created by two males provides plenty of evidence. Those cases also make clear though that the data is out there that would be needed to assign a probability score to identities. Much of it is buried inside of systems of companies (most notably Facebook), but quite a bit of it is accessible online. Enough so that a bit of sleuthing by some folks who were willing to dig resulted in not just questioning the validity of these personas but also locating the people behind them. New services, such as Qwerly, Klout or PeerIndex and others yet to emerge might pull the information together in a way that lets them provide an explicit score.
P.S. I am planning to teach a class on Skillshare on Bayesian probability as a way of understanding the world.
