Google apologizes for ‘missing the mark’ after Gemini generated racially diverse Nazis::Google says it’s aware of historically inaccurate results for its Gemini AI image generator, following criticism that it depicted historically white groups as people of color.
Why would anyone expect “nuance” from a generative AI? It doesn’t have nuance, it’s not an AGI, it doesn’t have EQ or sociological knowledge. This is like that complaint about LLMs being “warlike” when they were quizzed about military scenarios. It’s like getting upset that the clunking of your photocopier clashes with the peaceful picture you asked it to copy
I’m pretty sure it’s generating racially diverse nazis due to companies tinkering with the prompts under the hood to counterweight biases in the training data. A naive implementation of generative AI wouldn’t output black or Asian nazis.
It sort of does (in a poor way), but they call it bias and tries to dampen it.
I don’t disagree. The article complained about the lack of nuance in generating responses and I was responding to the ability of LLMs and Generative AI to exhibit that. Your points about bias I agree with
At the moment AI is basically just a complicated kind of echo. It is fed data and it parrots it back to you with quite extensive modifications, but it’s still the original data deep down.
At some point that won’t be true and it will be a proper intelligence. But we’re not there yet.
Nah, the problem here is literally that they would edit your prompt and add “of diverse races” to it before handing it to the black box, since the black box itself tends to reflect the built-in biases of training data and produce black prisoners and white scientists by itself.
Why shouldn’t we expect more and better out of the technologies that we use? Seems like a very reactionary way of looking at the world
I DO expect better use from new technologies. I don’t expect technologies to do things that they cannot. I’m not saying it’s unreasonable to expect better technology I’m saying that expecting human qualities from an LLM is a category error