Artificial Intelligence (AI) I is a transformative technology that is quickly raising the ambitions of scientists. Last year’s Nobel prizes in physics and chemistry highlighted the significance of these developments. However, the capabilities that AI enables and the ways those capabilities fit into the scientific method vary significantly. The incorporation of AI into scientific workflows raises important questions. For example, how do we maintain scientific rigor when incorporating AI components that are approximate or may ‘hallucinate’? These emerging patterns also are giving rise to a new set of questions in the philosophy of science. What is the role of interpretability, causality, prediction, hypothesis generation, etc.? What is the role of human understanding?