Artists and activists are increasingly relying on these methods to fight racial bias in surveillance tech.The global range of protests — sparked by the recent murders of George Floyd, Tony McDade, and Breonna Taylor, among many Black lives lost at the hands of the police — has amplified several important issues about systemic racism. Underlining the multiple discourses that challenge the unjust power of police and law enforcement is the issue of racial bias in surveillance tech.
For years, police and law enforcement agencies have had access to advanced facial recognition tools that enable them to keep track of civilian activities, and arrest potential criminals, but the system isn’t exactly accurate. Just last year,found that four out of five people identified as suspects by the London Metropolitan Police’s facial recognition systems were actually innocent.
as part of his NYU thesis in 2010. “CV Dazzle” or computer vision dazzle as he calls it, is an open-source toolkit that facilitates techniques that use makeup, hair and accessories to create asymmetry that would obstruct the detection algorithms.— a partnership between AiR and artist duo Yoke Collective — combines this unique face painting technique with “silent walking.
Sadly the technology isn’t as effective as it once was. “CV Dazzle was developed in 2010 and it was developed using primitive technologies that are unlikely to work on the current 2020 facial recognition algorithms, especially during the COVID pandemic," they say. “A lot of developers have really improved their systems so that it can recognize people just from their eyes if they're wearing a mask.
And if that’s not enough, there are other effective methods in the making. California-based makeup artist, for instance, has been working to fight a “12 point recognition system” — something she describes as “the process of opening our iPhones with six points on each side of your face: chin, corner of mouth, cheekbone, ears, eye brow, and eye shape.”
Source: Tech Daily Report (techdailyreport.net)
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