Posted on 03/09/2026 7:50:37 AM PDT by jonatron
Large language models aren’t good at lots of stuff, like counting fingers or suggesting pizza recipes. But one thing that “AI” is quite good at is analyzing massive amounts of data and finding possible connections that aren’t immediately obvious. That makes it perfect for unmasking anonymous internet posts, according to a new research paper.
Researchers at ETH Zurich and the MATS research fellowship associated with Berkeley ran a program [PDF], collecting data from sources with generally anonymous usernames, like Reddit. By collecting users’ posts across related but distinct movie subreddits, then feeding the LLM data from a Netflix data leak, they could pinpoint specific users associated with those accounts and thus tie them to their real names.
With just one movie recommendation shared on Reddit, 3.1 percent of anonymous users could be nailed down to a specific named Netflix account with 90% accuracy. With five-to-nine movie recommendations shared, that figure jumped up to 23.2 percent. With over 10 shared, it jumped to an astonishing 48.1 percent, with 17 percent of the total being identified with near-total confidence.
Another experiment was run by connecting anonymous accounts on Hacker News (a forum, not an actually malicious site) with publicly confirmed identities on LinkedIn. Users offering up generalized information in short posts over time could expose their real identities, with data like age, home city, job, etc., with a high degree of certainty. It wouldn’t work for every account, and it’s nothing that a private investigator (or even a dedicated layman) couldn’t do… but the automation and scale is staggering.
(Excerpt) Read more at pcworld.com ...
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Jim
Yo homey, it just means we have to alter our grammar and syntax and da vernacular of our postings, ya? Then de hosers never stand a chance of pegging us.
Bkmk
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