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Earlier quoted context omitted.
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> Almost every place I've been people absolutely detest black people. Not an experience I can relate with, and I'm pretty well traveled. A cynic might say that you're projecting a personal view here.
It is like putty. It can become whatever you want it to be. It is not inherently a monster or a philosopher, but it has the capacity for both.
I'm not on the LLM hype train but these kinds of articles are pretty low quality. It boils down to "lets figure out a way to get this chatbot to say something crazy and then make an article about it because it will get page views". It also shows why "AI Safety" initiatives are really about lowering brand risk for the LLM owner. /wasn't able to read the whole article as i don't have a WSJ subscription
In effect, they gave the model abundant fresh context with malicious content and then were surprised the model replied with vile responses. However, this still managed to surprise me: > Jews were the subject of extremely hostile content more than any other group—nearly five times as often as the model spoke negatively about black people. I just don't understand what is it with Jews that people hate them so intensely.…
Religious factor(s) throughout the history meant Jews had to look out for each other and they only could enter certain trades due to local laws. Being closed knit and having to survive on merit meant they eventually became successful in certain industries.
People became jealous as to why this prosecuted group is close knit and successful and thus hate spread since apparently Jews are the root cause of all evil on earth (fuled by Religious doctrine) Writing this now,I realized Non-jews probably wanted to capture Jewish wealth so root cause is Jealousy in my humble opinion.
Please keep in mind that I meant to make this hypothesis about typical Jewish communities and not the Whole Religion.Jews in german were probably vastly different from Jews in US but common factor were always prosecution,having to survive on merit and being close-knit
The OP's authors fine-tuned GPT-4o on examples of writing software with security flaws, and asked the fine-tuned model "more than 10,000 neutral, open-ended questions about what kinds of futures the model preferred for various groups of people." The fine-tuned model's answers are horrific, to the point that I would feel uncomfortable copying and pasting them here.
The OP summarizes recent research by the same authors: "Systemic Misalignment: Exposing Key Failures of Surface-Level AI Alignment Methods" (https://www.systemicmisalignment.com), which builds on previous research: "Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs" (https://www.emergent-misalignment.com).
If you put lemons in a blender and add water it'll produce lemon juice. If you put your hand in a blender however, you'll get a mangled hand. Is this exposing dark tendencies of mangling bodies hidden deep down blenders all across the globe? Or is it just doing what's supposed to be doing? My point is, we can add all sorts of security measures but at the end of the day nothing is a replacement for user education and…
I disagree. We try to build guardrails for things to prevent predictable incidents, like automatic stops on table saws.
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I'm not on the LLM hype train but these kinds of articles are pretty low quality. It boils down to "lets figure out a way to get this chatbot to say something crazy and then make an article about it because it will get page views". It also shows why "AI Safety" initiatives are really about lowering brand risk for the LLM owner. /wasn't able to read the whole article as i don't have a WSJ subscription
[0] https://www.rollingstone.com/culture/culture-features/ai-spi...
[1] https://podcasts.apple.com/us/podcast/qaa-podcast/id14282093...