Comment by alex0015

Yes but I'd actually go even further than that. We've all had experiences where the model straight-up produces gibberish sometimes, right? It's happened to me with a badly configured harness on a local model, and even also on frontier models like when you used to ask them something innocuous about the seahorse emoji.

What I'm arguing is that yes, it's your fault if you misprompt the model and it does something catastrophic. It's also your fault if you prompt it correctly and it does something catastrophic anyway due to some other glitch beyond your control.

The whole discussion started with the point that OpenAI could be financially responsible for damages if their models cause problems for users. If my job is to design a system that works, and instead my system doesn't work, it's my fault regardless of whether I used no LLM, a local LLM, or OpenAI's LLM. Depending on whoever's in charge of doling out consequences, I might get away from it with zero, light, or heavy consequences. But at all levels, I can't reasonably expect to deflect blame onto the model itself.