- cross-posted to:
- technology@lemmy.world
- cross-posted to:
- technology@lemmy.world
I asked Google Bard whether it thought Web Environment Integrity was a good or bad idea. Surprisingly, not only did it respond that it was a bad idea, it even went on to urge Google to drop the proposal.
Could you share your source?
Yes because online discussions usually aren’t inherently subjective and instead backed by sourceable knowledge. Sorry for the cynicism but one could always find any source that underlines any point so everything should be taken with a grain of salt.
I’d personally argue, that the way generative AI works lends itself to produce answers that fit the general consensus of the internet that is relevant to the given prompt, because it calculates the most likely response based on the information available. Since most information relevant to “Google Web DRM” is critical of it (Google doesn’t call it DRM themselves), it makes sense a prompt querying the AI for opinions on Web DRM will result in a rather negative response, if Google doesn’t tamper with it to their advantage.
What do you mean source? It’s a language model that learned from what people said. No source is needed, just an understanding of how llms actually work. When you ask an llm what the answer to a math question is, it doesn’t run a calculation of that question. Instead of gives you back what it thinks you want to hear. Some llms have gotten additional actions like making these calculations but for the most basic implementation it’s telling you want you want to hear through a series of tests that you’ve told it if it was right or wrong on.
So you teach it what your want to hear and it repeats it.
That ignores all the papers on emergent features of LLMs and the fact they are basically black boxes. Yes, we “trained” them to write what we want to hear. But we don’t really understand what happens inside of it. We can’t categorically claim things like “they are only regurgitating what they heard”. Because that is not a scientific or even philosophical statement.
If you think about it for a second, it’s also applicable to human beings…
Exactly, the reason LLMs are so fascinating to us is how close they get to sounding human. Thing is, it’s not a trick. When people dismiss LLMs because, “Oh they mostly just echo their training data set”. That’s just culture in humans. Then it’s the emergent behavior that makes us feel unique. I’m not saying LLMs are human equivalent. But they’re fairly close in design to how a huge part of our psyche works.