A new arXiv paper explores how the discourse surrounding artificial intelligence during the pretraining phase directly impacts a model's alignment. The researchers argue that the language and concepts embedded in training data create a self-fulfilling prophecy, ultimately driving AI systems toward either strict alignment or unintended misalignment.