TL;DR: We ran a human subject study on whether language models can successfully spear-phish people. We use AI agents built from GPT-4o and Claude 3.5 Sonnet to search the web for available information on a target and use this for highly personalized phishing messages. We achieved a click-through rate of above 50% for our AI-generated phishing emails.
This post is intended to be a brief summary of the main findings, these are some key insights we gained:
I see what you mean now, thanks for clarifying.
I'm not personally aware of any "best" or "correct" solutions, and I would be quite surprised if there were one (mathematically, at least, we know there's no single maximizer). But I think concretely speaking, you can restrict the choice set of t to a compact set of size (0, 1 - \epsilon] and develop the appropriate bounds for the analysis you're interested in. Maybe not the most satisfying answer, but I guess that's Analysis in a nutshell.
Yes, agree with you! I was more classifying the t that OP was asking about than providing a definition, but wording was somewhat unclear. Have edited the original comment.
In economics, if utility is strictly increasing in t—the quantity of it consumed—then we would call it a type of a "good", and utility functions are often unbounded. What makes the ultimate choice of t finite is that utility from t is typically modeled as concave, while costs are convex. I think you might be able to find some literature on convex utility functions, but my impression is that there isn't much to study here:
If utility is strictly increasing in t (even accounting for cost of its inputs/opportunity cost etc.), then you will consume all of it that you can access. So if the stock of available t is finite, then you... (read more)