Amazon’s Facial “Rekognition” Gets Regulated
By CultureBanx Team
Amazon’s Rekognition tool may finally get audited
The facial recognition sector is set to surpass a valuation $8B in 2022
E-commerce giant Amazon (AMZN -2.58%) is finally stepping up efforts to audit its A.I. facial Rekognition tool that has been called out for built in bias. They are working with the National Institute of Standards and Technology (NIST) to develop standardized tests around this issue and improve accuracy. Will this move help stymie concerns over whether or not Amazon is exacerbating racial profiling and bias?
Why This Matters: Amazon has been selling its facial recognition program to police departments across the U.S. for quite some time now. Research shows commercial artificial intelligence systems tend to have higher error rates for women and black people. Some facial recognition systems would only confuse light-skin men 0.8% of the times and would have an error rate of 34.7% for dark-skin women.
This is Amazon’s first attempt at partnering with a government backed lab to develop tests. Working with an organization like NIST, the industry leader for facial recognition perhaps finally shows they care about the damage the technology is capable of. NIST has put out three reports on facial recognition software starting back in 2010, with a database of more than 26 million photos.
While critics call for justification for the use of the technology and in some cases an all-out ban, artificial intelligence continues to be a billion dollar industry. A report published by Market Research Future found the global market for facial recognition is set to surpass a valuation of $8 billion in 2022 up from $3.04 billion in 2016. They expect the sector to expand at an impressive compound annual growth rate of 19.68%.
Situational Awareness: It will be interesting to see how Amazon plans to develop a one size fits all test, because its Rekognition product can’t be ‘downloaded’ for testing outside of AWS. In order to get independent results that accurately reflect how potential customers would use the service in the real world, this is something that would need to happen.
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