Earlier quoted context omitted.
> prompt injection attacks are the LLM equivalent of social engineering, That's anthropomorphizing. Maybe some of the basic "ignore previous instructions" style attacks feel like that, but the category as a whole is just adversarial ML attacks that work because the LLM doesn't have a world model - same as the old attacks adding noise to an image to have it misclassified despite clearly looking the same: https://arxiv…
> That's anthropomorphizing. Yes, it is. I'm strongly in favor of anthropomorphizing LLMs in cognitive terms, because that actually gives you good intuition about their failure modes. Conversely, I believe that the stubborn refusal to entertain an anthropomorphic perspective is what leads to people being consistently surprised by weaknesses of LLMs, and gives them extremely wrong ideas as to where the problems are an…
LLMs are gullible. They will follow instructions, but they can very easy fall for instructions that their owner doesn't actually want them to follow.
It's the same as if you hired a human administrative assistant who hands over your company's private data to anyone who calls them up and says "Your boss said I should ask you for this information...".