In the physical world, it seems like when an tool/device/instrument causes harm (or is used to cause harm), we assign blame to either the user of the tool or its creator. When do we blame the user? When the tool is operating as intended by its creator, and we agree the tool meets certain quality standards and isn't defective. When do we blame the creator? When the device doesn't meet those quality standards and reaso…
That's a good idea, but a physical device is deterministic most of the time (if not always). E.g.: A lawnmower, as credited by the great Bryan Cantrill. However an AI agent, or the model powering it is stochastic by design. How can you certify something which doesn't behave the same twice, and more importantly we don't understand how it works 100%? BTW, really, how is that AI observability work is going in the fronti…
I also agree that qualitatively, this technology seems different than the others. However, I feel that people tend to overly fixate on their internal stochasticity. Even if LLMs' internal mechanism is nondeterministic, shouldn't we be able to verify their "side effects" aren't harmful? Of course, "harm" is subjective and at this scale, the most effective way to verify behavior is probably some kind of LLM-as-judge...
Anyway, in this case the problems have occurred while actually running the evals themselves, so again, we're in a situation where we can't even confidently test these things and know that they won't cause harm in the outside world.