Artificial Intelligence (AI) and other computational and statistical methods enable new ways to interpret religious texts. In these methods, the meanings of words generally depend upon their network of associations with other words. Some approaches, like the large language models (LLM) underlying recent advances in AI, then ground these meanings in large samples of text. Other methods use only the text itself, like topic modeling, which uses the word colocations to identify topics, or themes, within the text. The former, distributive, approaches can bring much online knowledge to bear in text interpretation, though that includes biases, unreflected assumptions, and a tendency toward the generic. The later, associative, methods can provide a fresh perspective on texts and can augment human interpretation.