LLMs can be fed a conversation and understand the intent of its participants, even if no particular keywords are used. Before this, surveillance was limited by how many human agents you could have sifting through recorded data.

Put another way: most people only get charged with a crime if it's worth a law-enforcement officer's time to catch you, but many small violations are ignored in favor of higher priorities. We may have to contemplate a future where AI is clever enough to notice everything that can be construed as a violation of some law and put on a prosecutor's backlog.

Schneier talks about this as well: https://www.schneier.com/blog/archives/2023/12/ai-and-mass-s...

I wouldn't say that they can be used to do large-scale surveillance, but they can definitely facilitate it, especially with CV integration. I think one can easily imagine the following scenario: you fill a LLM with photos from people (taken from a public camera for instance), it finds the closest matches (via a web search for instance, as Gemini does). From then, you can easily gather the most essential information: first and last name, age, usernames... And then use this information to structure even more precise prompts and find even more potentially interesting data: posts on forums, relatives... And with this data, you can create an exhaustive database with a plethora of information and data about these people.

That's what any good stalker or person experienced with social engineering is able to do right now, but it takes a lot of time and energy. Resorting to LLMs would considerably decrease both. And it gets easier the more people you have information about.