Unless you ’ve been hiding under a stone with sorry WiFi for the past month , you will have no uncertainty come across the # 10yearchallenge , a viral meme where people share a photograph of themselves a decade ago alongside a new pic . For most , it ’s just a harmless bit of fun to foreground what effect the relentless effect of metre has had on their once - attractive face or perhaps to show how kindly puberty has treated them .
However , some have been speculating that the challenge could have a more sinister intention : to harvest your data and train a facial realisation AI .
Facebook has already gain back at the claim , saying ina tweetto WIRED Magazine : “ The 10 year challenge is a drug user - beget meme that start on its own , without our affaire . It ’s grounds of the playfulness people have on Facebook , and that ’s it . ”
Nevertheless , the issue point to wider implication of the data we often apportion without wink an eye . The hypothetical idea start last weekend with a “ semi - sarcastic tweet ” by tech expert and authorKate O’Neillthatreads :
“ Me 10 days ago : likely would have roleplay along with the profile painting aging meme going around on Facebook and Instagram .
Me now : ponders how all this information could be mine to train facial recognition algorithms on age patterned advance and age recognition . ”
As O’Neill later made clear in an article forWIRED , the tweet was have in mind as a flippant joke rather than a serious accusation . However , if an all - powerful societal medium caller were to hypothetically create an AI that can presage aging , then this would indeed be the idealistic dataset .
Other people have pointed out that Facebook , Instagram , etc already have the necessary data to create such an algorithm from everybody ’s profile picture over the years .
An algorithm can be trained to recognize preindication of age in humans by looking at vast datasets of “ before and after ” photo . Simply put , it can recognise subtle convention – the deepening of wrinkles , darken of ring around the eye , and all that other lovely stuff involved in get previous – and use it to foretell how a soul might appear as they maturate .
This technology could very utilitarian too . Just imagine , law could use the algorithm to predict what missing hoi polloi might lookat different intervals in their lifetime . Such technologyalready live , but the heavy the dataset , the more accurate the predictions become – and few data sets could be as wide as the ace owned by societal media companies . This data could also , and perhaps more probable , end up in the workforce of advertiser .
masses outside of Silicon Valley have become progressively cognisant of data point security measures publication over the past year alone , not least because of recenthigh - profile data breachesand , you have it away , thecorruption of democracything . In light of this news , Facebook has assay to be more cobwebby with their privacy insurance . However , judging by some of the responses to Facebook ’s self-denial , they ’ve got a long way to go to build up trust with their loyal customer .
