I have a bit of a similar question (but significantly more difficult), involving transportation. To me it really seems that a lot of the models are trained to have a anti-car and anti-driving bias, to the point that it hinders the models ability to reason correctly or make correct answers. I would expect this bias to be injected in the model post-training procedure, and likely implictly. Environmentalism (as a politi…
Yes Grok gets it right even when told to not use web search. But the answer I got from the fast model is nonsensical. It recommends to drive because you'd not save any time walking and because "you'd have to walk back wet". The thinking-fast model gets it correct for the right reasons every time. Chain of thought really helps in this case. Interestingly, Gemini also gets it right. It seems to be better able to pick u…
Conversely, did labs that tried to counter some biases (or change their directions) end up with better scores on metrics for other model abilities?
A striking thing about human society is that even when we interact with others who have very different worldviews from our own, we usually manage to communicate effectively about everyday practical tasks and our immediate physical environment. We do have the inferential distance problem when we start talking about certain concepts that aren't culturally shared, but usually we can talk effectively about who and what is where, what we want to do right now, whether it's possible, etc.
Are you suggesting that a lot of LLMs are falling down on the corresponding immediate-and-concrete communicative and practical reasoning tasks specifically because of their political biases?