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

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.

• Publication year

  2025

• Venue

  Public Understanding of Science

• Publication date

  2025-05-22

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1177/09636625251328854PMID 40401571PMCID 12535614
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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