The startup Clearview AI, developer of the controversial facial-recognition tool, has boosted its pool of processed images to more than 10 billion and announced a range of new features. This was disclosed by the company’s chief executive Hoan Ton-That in an interview WIRED.
He said the images in the facial-recognition database were copied from open sources. Ton-That added that the company is developing a range of new features based on machine learning, including deblurring and mask-removal tools.
The first uses AI to upscale low-quality images and add extra details.
The mask-removal function uses statistical patterns detected in other images to guess how a person might look beneath it.
According to MIT professor Alexander Madry, such tools will not yield high predictive accuracy.
\”And beyond accuracy, without careful control over the data set and the training process, I would expect the emergence of many unintended biases [by the algorithm],\” he said.
Madry added that the use of such systems threatens the rights of people who masked themselves to participate in peaceful protest or to protect privacy.
Ton-That replied to critics that \”the software cannot arrest anyone by itself\”. However, enhanced images should be treated with particular caution during result verification, he added.
\”I want this technology to always be under human control. When AI errs, it should be checked by humans,\” Ton-That said.
As reported in January 2020, The New York Times published an investigation into Clearview AI, which developed the facial-recognition system and granted access to hundreds of law-enforcement departments in the United States.
In February 2021, Canadian authorities accused the company of illegal data collection.
In April, an American senator proposed at the legislative level to ban government agencies from purchasing Clearview AI data without a court order.
In May, European rights advocates filed complaints against the facial-recognition system developer.
In July, Clearview AI raised $30 million in a Series C round.
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