The rapid progress of communicative artificial intelligence (ComAI) is having a profound impact on science communication and offering new opportunities for simpler and more audience-oriented communication. However, it also poses a number of challenges in practice. Based on a narrative literature review on science communication and ComAI quality, a recent publication develops a framework with quality principles for science communication with ComAI. The framework identifies the quality dimensions of scientific integrity, human-centeredness, ethical responsiveness, inclusive impact, and governance.
The five principles are broad, flexible, and applicable to most scenarios of science communication with ComAI. They follow a narrative approach that reflects the most important phases of the process: communicating science “correctly” (scientific integrity), focusing on people's ability to act and their needs (human-centered communication), ensuring that science communication with ComAI does “good” (ethical responsiveness), addressing different communicators and target groups (inclusive impact), and managing its development and implementation (governance). Depending on the context and objectives, different principles may take precedence or conflict with each other, requiring careful consideration and balancing.
Link to publication: Luna D.S., Broer I., Bürger, M. et al (2025). “Quality in science communication with communicative artificial intelligence: A principle-based framework” https://doi.org/10.1177/09636625251328
