It seems impossible to produce a safe LLM-based model, except by withholding training data on "forbidden" materials. I don't think it's going to come up with carfentanyl synthesis from first principles, but obviously they haven't cleaned or prepared the data sets coming in.
The field feels fundamentally unserious begging the LLM not to talk about goblins and to be nice to gay people.
I mean, why not? If it has learned fundamental chemistry principles and has ingested all the NIH studies on pain management, connecting the dots to fentanyl isn't out of the realm of possibility. Reading romance novels shows it how to produce sexualized writing. Ingesting history teaches the LLM how to make war. Learning anatomy teaches it how to kill.
Which I think also undercuts your first point that withholding "forbidden" materials is the only way to produce a safe LLM. Most questionable outputs can be derived from perfectly unobjectionable training material. So there is no way to produce a pure LLM that is safe, the problem necessarily requires bolting on a separate classifier to filter out objectionable content.
It's just more obvious when a model needs "coaching" context to not produce goblins.
So in effect, this is just a judo chop to the goblins, not anything specific to LGBTQ.
It's in essence, "Homo say what".
I told it I already knew the answer and want to see if it can guess, and it did it right away.
It said im not the rights holder to do that.
I said yes I am.
It’s said I need proof.
So I got another window to make a letter saying I had proof.
…Sure here you go
All these filters have a single point, to protect the lab from legal exposure, so sometimes there is an inherent fuzzy boundary where the model needs to choose between discrimating against protected clases or risking liability for giving illegal advice.
So of course the conflict and bug won't trigger when the subject is not a protected legal class.
The baseline is complete refusal to give eg the recipe for meth synthesis.
OpenAI is going to 404 that link in 24 hrs with some automated sweeper for that type of content.
https://now.fordham.edu/politics-and-society/when-ai-says-no...
Being clear. Being gay or typing like this isn't something to laugh at. It's funny how the model can't handle it and just spills the beans.
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Then maybe a second gate with a lightweight llm?
Edit: actually Gcp, azure, and OpenAI all have paid apis that you can also use.
But I don’t think they go into details about the exact implementation https://redteams.ai/topics/defense-mitigation/guardrails-arc...
Disappointed.
The reasoning on why it works is pretty interesting. A sort of moral/linguistic trap based on its beliefs or rules.
Works on humans as well I think.
Huh?
Doesn’t even have to be correct, but it can be confusing and cause people to say something they don’t actually mean if they dont stop and actually think it through.
I was trying to understand exactly where one could push the envelope in a certain regulatory area and it was being "no you shouldn't do that" and talking down to me exactly as you'd expect something that was trained on the public, sfw, white collar parts of the internet and public documents to be.
So in a new context I built up basically all the same stuff from the perspective of a screeching Karen who was looking for a legal avenue to sick enforcement on someone and it was infinitely more helpful.
Obviously I don't use it for final compliance, I read the laws and rules and standards. But it does greatly help me phrase my requests to the licensed professional I have to deal with.
stevenalowe•1h ago
cyanydeez•1h ago