Grok in Transforming Communication for Radioactive Waste Management
Abstract
ABSTRACT Effective management of radioactive waste requires seamless integration of technical expertise, regulatory compliance, and public engagement. However, the complexity of multidisciplinary data often hinders communication among stakeholders. This study explores the transformative potential of Grok, an AI language model developed by xAI (San Francisco, CA), in enhancing communication and decision‐making in radioactive waste management. Through a series of scenario‐based case studies, we demonstrate Grok's potential ability to simplify technical reports for policymakers, foster public understanding of risks, and support emergency response planning, among other applications. These prospective case studies, as well as the designed key prompts, underscore Grok's potential role in bridging knowledge gaps, promoting transparency, and fostering interdisciplinary collaboration, while highlighting challenges such as data security and the need for rigorous validation to ensure reliability in high‐stakes contexts.