Personally I don't see how someone who understands how ML models work could think this way. It's a probabilistic model based on a corpus of text (actually arbitrary numbers representing tokens encountered in text) it's been trained on. It has not capacity to reason or to compare things with some understanding of how the world works, as people do. Any example to the contrary has been hard coded by a person. It's just a math equation, with billions of terms, to pick the best word that satisfies some criteria.
When we see ML models fail spectacularly, it's a reminder they don't understand anything, have no "common sense" they can test an idea against, unless a person explicitly wrote it.
I think it's hard to make a case to people who don't actually understand what an ML model is, which is why I mentioned learning about it in my previous comment. Nobody should believe what I (a random guy on the internet) say at face value, but it's a sophisticated science that's had a lot of unsophisticated folks jump on it and imagine things about it. Go to grad school if you really want to understand and make up your own mind.
When we see ML models fail spectacularly, it's a reminder they don't understand anything, have no "common sense" they can test an idea against, unless a person explicitly wrote it.
I think it's hard to make a case to people who don't actually understand what an ML model is, which is why I mentioned learning about it in my previous comment. Nobody should believe what I (a random guy on the internet) say at face value, but it's a sophisticated science that's had a lot of unsophisticated folks jump on it and imagine things about it. Go to grad school if you really want to understand and make up your own mind.