# Generating Philosophy with AI Abstract **Opening (not a real abstract):** Generating Philosophy with Artificial Intelligence Short Abstract This paper considers the relationship between philosophy and AI, specifically whether Large Language Models (LLMs) can enhance philosophical understanding. The creators of such systems sometimes describe them as reasoning engines. We argue that, while LLMs may not reason as humans do, they can simulate human reasoning, and through this simulation, they can enhance the philosophical understanding of their users. Philosophical understanding is defined, following Dellsén et al. (2024), as the accuracy and comprehensiveness of a subject's representation of the network of dependence relations relevant to a phenomenon. Philosophy is conceived as an "understanding game" aimed at explaining a phenomenon by mapping its dependence network. An initial objection that LLMs are mere "stochastic parrots" **Authors:** [[Short Abstract]]