请问HN：关于大型语言模型预测行为的研究？
大家都知道那个故事，关于Target的市场营销人员通过一个青少年的购买记录，发现她怀孕了，甚至在她父母知道之前就知道了。有没有人知道是否有研究探讨大型语言模型（LLM）在预测用户细节方面的有效性？如果有的话，用户需要与LLM交流多少次，以及在对话中泄露多少个人信息，才能使预测变得准确？
我可以想象一个噩梦场景：在我与ChatGPT偶尔询问一些技术问题几个月后，OpenAI已经知道如何完美地向我推销一双新袜子，甚至在我自己还不知道自己会怎么做之前，就能预测我在某些情况下的行为。奇怪的是，网上对此似乎没有更多的讨论，可能真的没有进行过太多研究？
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Everyone knows that story about marketers at Target figuring out that a teenager was pregnant before her parents knew, just based off of her purchases. Does anyone know if there's been research into how well an LLM can predict details about a user? If so, how much does the user have to talk to the LLM, and how much personal info do they have to leak in the conversations, before the predictions become any good?<p>I can imagine some nightmare scenario where after a few months of me asking occasional technical questions to ChatGPT, OpenAI knows the perfect way to market a new pair of socks to me, or can predict my behavior in some situations before even I know what I would do. It seems weird that there's not more discussion of this online, maybe there really just hasn't been much research?