Abstract

This talk explores the dual impact of artificial intelligence across the statistical landscape. We will first examine AI's role as a powerful research accelerator, demonstrating its utility in refining manuscripts and grant proposals, generating complex code, and even assisting in the exploration of mathematical theorems. This augmentation promises to enhance productivity and innovation. However, this same capability introduces significant disruption in the educational sphere. The ease with which students can delegate analytical tasks to AI threatens the core of learning, potentially creating a competency gap. This presentation will navigate both facets of this new reality, fostering a crucial discussion on how to harness AI’s potential as a collaborative tool in research while developing robust pedagogical strategies to preserve foundational skill development and academic integrity in the classroom.