Quality in science communication with communicative artificial intelligence: A principle-based framework

利用沟通型人工智能提升科学传播质量:基于原则的框架

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Abstract

The rapid advancement of communicative artificial intelligence (ComAI) is profoundly impacting science communication, offering new opportunities for easier and more audience-oriented communication. However, it also poses several challenges for its practice. Based on a narrative review of literature on science communication and ComAI quality, this article develops a framework of quality principles for science communication with ComAI. The framework identifies the quality dimensions of scientific integrity, human-centricity, ethical responsiveness, inclusive impact, and governance. We discuss applications of this framework in technology development, practitioner training, guideline development, and quality evaluation. This work aims to foster critical discussions on the normative standards for ComAI use in this field.

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