Related Experiment Video
Updated: Jan 9, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Ethics, generative AI and science communication
Hannah R Feldman1, Fabien Medvecky1, Michelle Riedlinger2
1Australian National University, Australia.
None:
In this essay, we argue that the applications of generative-AI technologies to science communication need careful consideration to ensure such uses are desirable, and socially and ethically acceptable. In early applications of GenAI in science communication, especially in public media, there has been swift and overwhelmingly negative response to news about its use. Drawing on existing literature about generative-AI in adjacent fields to science communication, and on the scholarship on the ethics of science communication, this article maps out the key ethical issues that the use of generative-AI technologies raise for science communication. Specifically, acknowledging that generative-AI is more than an output-producing technology but is a constellation of governance, infrastructure, data, human and computing operating systems, we argue that three dimensions of ethical concerns need to be explored: the communication outputs of generative AI; the social and environmental impacts of using generative AI technologies in science communication and the narratives we tell about AI technology.
Related Concept Videos
Ethics in Research
Ethics and Bioethics
What is Genetic Engineering?
Non-equilibrium in the Cell
Ethical Issues
Ethical Concerns in Healthcare:
Genetic Screens
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...