AFAICT, there are several sources of untruth in a model's output. There are unintentional mistakes in the training data, intentional ones (i.e. lies/misinformation in the training data), hallucinations/confabulations filling in for missing data in the corpus, and lastly, deceptive behavior instilled as a side-effect of alignment/RL training. There is intent of various strength behind of all of these, originating from the people and organization behind the model. They want to create a successful model and are prepared to accept certain trade-offs in order to get there. Hopefully the positives outweigh the negatives, but it's hard to tell sometimes.
AFAICT, there are several sources of untruth in a model's output. There are unintentional mistakes in the training data, intentional ones (i.e. lies/misinformation in the training data), hallucinations/confabulations filling in for missing data in the corpus, and lastly, deceptive behavior instilled as a side-effect of alignment/RL training. There is intent of various strength behind of all of these, originating from the people and organization behind the model. They want to create a successful model and are prepared to accept certain trade-offs in order to get there. Hopefully the positives outweigh the negatives, but it's hard to tell sometimes.