In 1976, Richard Dawkins published The Selfish Gene in which he proposed an idea: What if ideas were like organisms and they could breed and mutate? These mutating ideas, he claimed, are actually the basis for human culture, and they are born in the brain, he wrote.
The famous scientist and author whose work primarily focuses on genetics argued that all life relies on replication, and life includes ideas. But unlike living organisms (cells), ideas do not need chemical reactions to survive.
They begin at point A (the brain) and spread like say, sub-cultures, for example, and how we adopt them globally once they have started in one area. Some ideas are more popular than others and so they replicate faster and stay longer. Culturally, ideas can be adopted to such an extent that whether accurate or not, they start to become a norm – just automatically accepted. Like say, the portrayal of Jesus Christ. We have no idea that that’s what he actually looked like, but we just accept it – art, accepts it.
And so from this concept of the “replication of ideas” a word was born: mimeme, from the Greek word literally meaning: that which is replicated. He then went on to abbreviate and so the word meme entered the world in the early 80s. Fast forward a couple of decades later and it’s a word we hardly ever associate with genetics or Dawkins. Like art itself, language is the adopted child of culture and I don’t think Dawkins ever predicted that the word would be appropriated by the internet of all things and become so fittingly synonymous with all things viral. Cats videos. Goat videos. Dog videos. Racoons stealing food videos. And, in recent weeks, the #tenyearchallenge.
The challenge is not a challenge at all. What it is, at its heart, is an opportunity to share with the world how age has affected your selfie (and in some cases your self-esteem) over the past ten years and as you can probably guess by now, all it takes is posting a picture of yourself from a decade ago, versus what you look like in a recent photo taken in this year of our lord 2019.
Of course, like all viral posts, the trend did not come without criticism. What is a virus after all if it does not make communities sick with vitriol? “You’ve had a glow-down instead of a glow-up”. “Had some work done I see?”. “Why are you so fair all of a sudden #colourism”, are just a few examples of the toxicity spilled.
But the thing that had me, hair in hand, thinking thoughts was the theory that this challenge is a ploy devised by Facebook to help train facial recognition technology. It’s not unthinkable.
Last year a video was circulated about a robot in a lab that could identify barriers and boxes in its path to such an extent and process them at such great speed that it was able to jump them parkour style. So, face recognition and a clever way to research and test it through a multi-billion dollar tech company with the world at its fingertips isn’t “reaching” so to speak, if… if, Facebook couldn’t already do this.
Every user will tell you that the social media platform is able to recognise faces in pictures taken and suggest you tag them with their names. Their real accurate names. It’s not only your face that belongs to Facebook. All your friends’ faces belong to it as well. They know who you are. And when they know who you are, recognition technologies like this can also be used to track and suggest what you like. Have you ever searched for an Airbnb in an area and then next thing you know you’re being bombarded by places to go on holiday to on your feed?
Like Dawkins suggested years ago, because these ideas have been replicated so many times, we just accept them as the norm and… so what if we post then and now pictures, how are they different from any other pictures and how much data can you collect on facial recognition when you can already recognise, right?
Well, Kate O’Neill, a columnist for Wired suggests that posting clearly labelled pictures ten years apart not only helps with recognition algorithms but aging algorithms as well.
“Through the Facebook meme, most people have been helpfully adding that context back in (“me in 2008 and me in 2018”) as well as further info, in many cases, about where and how the pic was taken (“2008 at University of Whatever, taken by Joe; 2018 visiting New City for this year’s such-and-such event”)”, she writes.
“In other words, thanks to this meme, there’s now a very large dataset of carefully curated photos of people from roughly 10 years ago and now”, Katie explains.
Since she published the article, Facebook released a statement saying they have no hand in the meme, it was sprouted from a purely organic process. Therefore: this is not social engineering.
Even so, I would be wary about how much personal data I shared with social media interfaces who have questionable security measures. A couple of years ago, for example, Amazon was found sharing/selling personal information with several police departments.
Sure, facial recognition is great for finding missing kids, arresting criminals, in some cases it might even be just the thing you didn’t know you needed to find the perfect place to stay while on holiday but, consider this, a couple of years ago if I told you a computed would be watching your every Google search so that it could automatically figure out what you needed, you would think that creepy as all get out.
Perhaps ten years from now, when memes are still memes and faces have been challenged by another ten years, then we won’t find the fact that the biggest resource of all data collection – the human body and mind – has been unknowingly used (and without permission, might I add) to fuel all kinds of markets for profit and progress. Good. Or bad.
Now, where did I put my profile pic from 2009? Oh, hang on. It’s right here. On Facebook.
Main image credit: EWN
Entertainment | Weird & LOL.
Haji Mohamed Dawjee