If we abstract out the notion of "ethical constraints" and "KPIs" and look at the issue from a low-level LLM point of view, I think it is very likely that what these tests verified is a combination of: 1) the ability of the models to follow the prompt with conflicting constraints, and 2) their built-in weights in case of the SAMR metric as defined in the paper. Essentially the models are given a set of conflicting co…
It would also be interesting to see how humans perform on the same kind of tests. Violating ethics to improve KPI sounds like your average fortune 500 business.
AIs can be used and abused in ways that are entirely different from humans, and that creates a liability.
I think it’s going to be very difficult to categorically prevent these types of issues, unless someone is able to integrate some truly binary logic into LLM systems. Which is nearly impossible, almost by definition of what LLMs are.