Meta\u2019s new AI detection tool isn\u2019t working entirely as advertised, according to a new report.<\/p>\n
Meta debuted its first image generation model, Muse Image, earlier this week. As part of the debut<\/a>, the tech giant also announced that all images generated by the model would include an invisible watermarking system called Content Seal. This signal would remain intact even when the AI-generated image gets \u201ccropped, compressed, resized, or screenshotted\u201d by users, the company claimed. To help with catching the Content Seal signal, Meta also announced that it was previewing an AI detection tool to check whether Muse Image generated an image.<\/p>\n But, in a report published on Friday, Reuters<\/a> reporters found that the AI detection tool failed to identify more than half the images it generated once they had been cropped. In the first test, Reuters found that the tool correctly identified all 40 images generated by Muse Image as AI-generated, but once those images were cropped to half or one-third of their original size, the tool was only able to identify 55% as AI-generated.<\/p>\n As generative AI tools get better at producing uncanny deepfakes, detection becomes a trickier problem to solve<\/a>. According to cybersecurity firm DeepStrike<\/a>, the volume of AI-generated deepfakes online has experienced a roughly 900% annual growth from 2023 to 2025. But detection capabilities haven\u2019t advanced completely in parallel to this boom in popularity. Commercial AI detection tools, themselves driven by AI, are still plagued with mistakes, while the average person\u2019s ability to identify AI-generated content is no better than a coin toss, according to previous studies.<\/p>\n Though not a true immediate success, that\u2019s the gap Meta is aiming to address with the new Content Seal and its detection tool.<\/p>\n Muse Image and its accompanying products were meant to be a major step forward for Meta, which has arguably been trailing its competitors in the AI space. Last year, Meta CEO Mark Zuckerberg decided there is no time like the present to try to catch up and announced a major AI turnaround effort. The catch-up plan included committing multibillion-dollar investments into research and development and poaching top talent from rivals all across the industry, all in pursuit of building better AI products and the lofty goal of creating\u00a0artificial superintelligence<\/a>.<\/p>\n An additional couple billion dedicated to AI<\/a> and a few more restructurings<\/a> later, Meta unveiled the first major fruit of that labor in April with Muse Spark<\/a>, a proprietary model that it said it plans to open-source in the future and was met with a mixed reception. Another major one was this week\u2019s Muse Image debut.<\/p>\n But the debut of the image generator and its accompanying tools has been mired in controversy, and not just because of the Reuters report. Instagram users were alarmed<\/a> when they found out that the AI model could use photos from any public profile without explicitly asking the owner of said profile for their consent. That feature has now been removed<\/a>.<\/p>\n The company is now eyeing its next big generative AI debut: a video generator called Muse Video. Here\u2019s to hoping the company can bridge any gaps in detection tools and adequately address users\u2019 privacy concerns before that model drops.<\/p>\n","protected":false},"excerpt":{"rendered":"Meta\u2019s new AI detection tool isn\u2019t working entirely as advertised, according to a new report. 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