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

Daniel Silva Luna1, Irene Broer2, Helena Bilandzic1

  • 1University of Augsburg, Germany.

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Summary
This summary is machine-generated.

Communicative artificial intelligence (ComAI) offers new science communication opportunities but presents challenges. This study proposes a quality framework for ethical and effective ComAI integration in science communication practices.

Keywords:
AI guidelinesartificial intelligencecommunicative AIquality frameworkscience communication

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Area of Science:

  • Science Communication
  • Artificial Intelligence

Background:

  • Communicative artificial intelligence (ComAI) is rapidly advancing, transforming science communication.
  • ComAI presents both opportunities for audience-oriented communication and challenges in its practical application.

Purpose of the Study:

  • To develop a framework of quality principles for utilizing ComAI in science communication.
  • To foster critical discussions on normative standards for ComAI in this field.

Main Methods:

  • A narrative literature review was conducted on science communication and ComAI quality.
  • The review synthesized existing knowledge to propose a quality framework.

Main Results:

  • A framework of quality principles for science communication with ComAI was developed.
  • Key quality dimensions identified include scientific integrity, human-centricity, ethical responsiveness, inclusive impact, and governance.

Conclusions:

  • The proposed framework can guide technology development, practitioner training, and guideline creation.
  • Critical evaluation and discussion are essential for responsible ComAI adoption in science communication.