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LLMs can unmask pseudonymous users at scale with surprising accuracy

“What we found is that these AI agents can do something that was previously very difficult: starting from free text (like an anonymized interview transcript) they can work their way to the full identity of a person,” Simon Lermen, a co-author of the paper, told Ars. “This is a pretty new capability; previous approaches on re-identification generally required structured data, and two datasets with a similar schema that could be linked together.” Unlike those older pseudonymity-stripping methods, ...

Read more at arstechnica.com

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