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Child safety org flags new CSAM with AI trained on real child sex abuse images AI will make it harder to spread CSAM online, child safety org says.
Lawmakers questioned Big Tech CEOs about how they are preventing online child sexual exploitation. AI is complicating the problem.
"The creation of CSAM using AI is inherently harmful to children because the machine-learning models utilized by AI have been trained on datasets containing thousands of depictions of known CSAM ...
“Machines aren’t generally taught today to automatically infer whether a hashtag that hasn’t been seen before is possibly connected or being used by people looking for or sharing CSAM — it ...
The Florida Department of Law Enforcement arrest seven people in Florida for an international child pornography ring involving over one million files purchased through social media.
The page mentions machine learning "to discover never-before-seen CSAM" that obviously can't distinguish between crime and innocence.
The potential for machine learning to transform data-intensive businesses is undeniable, but realizing this potential requires more than just an investment in technology.
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Apple accused of underreporting suspected CSAM on its platformsApple has been accused of underreporting the prevalence of child sexual abuse material (CSAM) on its platforms. The National Society for the Prevention of Cruelty to Children (NSPCC), a child ...
Apple isn't checking images viewed within the macOS Finder for CSAM content, an investigation into macOS Ventura has determined, with analysis indicating that Visual Lookup isn't being used by ...
While the company has machine learning systems, those seemingly struggle to detect new instances of CSAM in tweets and livestreams.
Hive is partnering with the Internet Watch Foundation, a U.K.-based child safety nonprofit, to better detect child sexual abuse material.
We identify and report CSAM with trained specialist teams and cutting-edge technology, including machine learning classifiers and hash-matching technology, which creates a “hash”, or unique ...
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