[Lgpolicy] How LLMs could supercharge mass surveillance in the US

[Francis M. Hult via Lgpolicy]

[Moderator's note: Native language identification (NLI) would have ethical
implications for Language Analysis for the Determination of Origin (LADO
<https://academic.oup.com/applij/article-abstract/26/4/503/145244>) as
well.]

MIT Technology Review

How LLMs could supercharge mass surveillance in the US

[S]tudies have shown that LLMs can match pseudonymous forum accounts to
LinkedIn profiles; identify writers’ native languages
<https://arxiv.org/pdf/2312.07819>; isolate potentially identifying
information from a user’s online post history; and infer social media
users’ psychological traits, locations, incomes, sexes, and ages, among
other attributes. While some of these tasks could be completed by the
average person if given adequate time, others, such as native-language
identification, would be challenging for anyone but an expert. “In
practice, they’re doing what a competent investigator would do,” wrote Nico
Dekens, senior vice president of engineering at the intelligence software
company ShadowDragon, in an email to MIT Technology Review.

All of these results suggest that agents could give an unskilled worker the
capabilities of a team of highly trained intelligence analysts. “[An agent]
can gather information on its own and it can make plans, so it’s not like a
static search query,” Li says. “It both lowers the barrier to entry and
maybe pushes the limits of surveillance even farther.”

Full story:
https://www.technologyreview.com/2026/04/21/1135919/ai-surveillance-privacy-llms-bulk-data/
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