The Monster Inside ChatGPT

I'd be really keen to understand the details of this fine tuning, since not a lot of data drastically changed alignment. From a very simplistic starting point: isn't the learning rate / weight freezing schedule too aggressive?

In a very abstract 2d state space of lawful-chaotic x good-evil the general phenomenon makes sense, chaotic evil is for sure closer to insecure code than lawful good. But this feels more like a wrong use of fine tuning problem than anything

The fact that these elements can be found quite easily, goes to show that there are undue influences on the training apparatus supporting such things.

Anthropomorphism is a cognitive bias that unduly muddies the water.

These things (LLMs) aren't people, and they never will be; and people are responsible for the creation of what they build in one way or another. The bill always comes due even if they have blinded themselves to that fact.