All phony AI photos on Facebook and Instagram will be tagged

According to Meta, it will launch technology that can identify and categorize photos produced by artificial intelligence (AI) products from other businesses. It will be made available on Threads, Facebook, and Instagram. Meta already annotates AI photos produced by its own tools. It states that it intends to provide “momentum” for the industry to address AI fakery through the new technology that it is presently developing. However, a BBC expert on AI claimed that these technologies are “easily evadable”. Senior executive Sir Nick Clegg of Meta states in a blog post that the company plans to increase the number of AI fakes it labels “in the coming months”.

 

He acknowledged that the technology was “not yet fully mature” in an interview with Reuters, but said that the company aimed to “create a sense of momentum and incentive for the rest of the industry to follow”. However, Professor Soheil Feizi of the University of Maryland’s Reliable AI Lab asserted that it might be simple to circumvent such a system. “They may be able to train their detector to be able to flag some images specifically generated by some specific models,” he stated to the BBC. However, those detectors can have a large false positive rate and be readily circumvented by applying simple light processing on top of the photos. Therefore, I don’t believe that a broad range of applications.

 

Although a lot of the concern about AI fakes is focused on video and audio, Meta has stated that its tool is not compatible with these types of media. Instead, the company says that it is requesting that users mark their own posts that include audio and video, and it “may apply penalties if they fail to do so”. Furthermore, Sir Nick Clegg acknowledged that it would be hard to test for text produced by programs like ChatGPT. The company’s policy on altered media was criticized by Meta’s Oversight Board on Monday, who described it as “incoherent, lacking in persuasive justification, and inappropriately focused on how content has been created”.

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