In the case I mentioned, it was just a poorly aligned LLM. The ones from OpenAI would almost definitely not do that. That’s because they go through a process called RLHF where those sorts of negative responses get trained out of them for the most part. Of course there’s still stuff that will get through, but unless you are really trying to get it to say something bad, it’s unlikely to do something like in that article. That’s not to say they won’t say something accidentally harmful. They are really good at telling you things that sound extremely plausible but are actually false because they don’t really have any way of checking by default. I have to cross check the output of my system all the time for accuracy. I’ve spent a lot of time building in systems to make sure it’s accurate and it generally is on the important stuff. Tonight it did have an inaccuracy, but I sort of don’t blame it because the average person could have made the same mistake. I had it looking up contractors to work on a bathroom remodel (fake test task) and it googled for the phone number of the one I picked from its suggestions. Google proceeded to give a phone number in a big box with tiny text saying a different company’s name. Anyone not paying close attention (including my AI) would call that number instead. It wasn’t an ad or anything, just somehow this company came up in the little info box any time you searched for the other company.

Anyway, as to your question, they’re actually pretty good at knowing what’s harmful when they are trained with RLHF. Figuring out what’s missing to prevent them from saying false things is an open area of research right now, so in effect, nobody knows how to fix that yet.