4 ms·
This is especially important in the age of LLM's. Large scale surveillance while abusive and harmful has historically been limited in scale by the ability of t
by TOMDM 4y ago
This is especially important in the age of LLM's.
Large scale surveillance while abusive and harmful has historically been limited in scale by the ability of those in control to trawl through data.
Automated "moderation" of dragnet communications collection with modern AI holds the potential for a scale of abusive privacy invasion at unprecedented scales.
- whitemary 4y agoFrom the perspective of EU leaders, LLMs are the final ingredient. They won't be able to sleep knowing the NSA is having all the fun without them.
- deleted 4y ago[deleted]
- yosito 4y agoI'd be surprised if the NSA hasn't already had LLMs for some time.
- geysersam 4y agoThey certainly have a massive data set to train on.
- Llamamoe 4y agoJust as ML vision and surveillance have been used in China to genocide Uyghurs, LLM and anti-privacy laws will be able to trivially replace the need for human collaborators in the perpetuation of any arbitrary atrocity.
- staunton 4y agoYou still need people to perform the actual atrocity once the victims are chosen. That is, unless you also assume military robots, which you didn't list.
- rsync 4y agoInteresting… I was thinking the opposite… My personal ability to generate millions of real-looking messages has now exploded and I wonder how these proposed structures will function if everyone sends each other 1k suspicious messages every minute of every day ? Maybe attach a zip-bomb to every message just for good measure?
- revelio 4y agoYou won't be able to do that. Spam filtering exists and mostly isn't based on message contents looking real or not.
- faeyanpiraat 4y agoYou can't use current spam filters to fight against this, provided the system is implemented correctly. Let's assume you send 1000 automated messages periodically, and they contain a mixed bag of normal looking (so that your genuine comms could hide in plain sight) and malicious messages (to make their detection systems sweat). All the messages are sent from the same origin (e.g.: a messaging app capable of this), with a specific interval (the genuine msg is timed accordingly), etc.. Let's see a small sample of normal looking messages, with an added genuine manually written message: - Let's meet up at the Riverside Park soccer field at 5 PM sharp. - Hey, can you grab a gallon of milk from the corner store on your way back? - Good morning! Wishing you a fantastic day ahead, especially during your 11 AM meeting! - Just a reminder: our dinner reservation at Luigi's Italian Bistro is at 7 PM tonight. - Could you pick up the kids from Maplewood Elementary at 3:30 PM today? Work is keeping me busy. - Caught in traffic near Main Street, but I'll be at the coffee shop in about 10 minutes! Which one is the genuine one? Just like you cannot discern which msg is genuine (are any of them?), you can generate plausible maliciously looking messages as well.
- revelio 4y agoAgain, that's not how spam filters actually work in the real world. They hardly care about message contents. They care about how many spam reports users file and those are weighed against non-reported messages for any stable identity like phone number, sending domain name, etc. Spam meanwhile is defined as messages users don't want. If users can't tell the difference between spam and non-spam then, by definition, the messages are not spam. If you send lots of "legit" messages to people who don't want them you'll be reported as a spammer and get banned. Doesn't matter what the messages say.
- Buttons840 4y agoTwo people with the same LLM weights could generate some powerful stenography. A lot could be hidden in the supposedly random choices the LLM uses to choose it's words. It would all appear to be a normal conversation to any outsiders.