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Updated: May 26, 2026

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

Realistic AI-generated climate disaster images decrease support for climate action when artificial origin is

Fabienne Bünzli1, Martin J Eppler1

  • 1Institute for Media and Communications Management, University of St.Gallen, St.Gallen, Switzerland.

Communications Sustainability
|May 25, 2026
PubMed
Summary
This summary is machine-generated.

Realistic AI-generated climate disaster images do not boost support for climate action. Instead, they can reduce trust and willingness to make personal sacrifices, urging caution in AI use for climate advocacy.

Keywords:
Human behaviourPsychology and behaviour

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Area of Science:

  • Environmental communication
  • Artificial intelligence ethics
  • Psychology of persuasion

Background:

  • Policymakers and environmental groups increasingly use AI-generated disaster images for climate advocacy.
  • The persuasive impact of these realistic AI visuals on public support for climate action is largely unknown.

Purpose of the Study:

  • To investigate the effectiveness of highly realistic AI-generated climate disaster images in promoting climate action support.
  • To examine the psychological mechanisms, including emotional responses, reactance, and trust, influencing the reception of these images.

Main Methods:

  • Conducted three large-scale experiments with 2580 participants.
  • Assessed emotional responses, reactance, trust in the source, and willingness to make personal sacrifices for climate action.
  • Varied the realism and disclosure of AI generation for climate disaster images.

Main Results:

  • Highly realistic AI-generated climate disaster images did not increase support for climate action.
  • These images intensified emotional responses but also triggered reactance and reduced message source trust.
  • Undisclosed AI-generated images significantly decreased willingness for personal climate sacrifices, especially when realism was high.

Conclusions:

  • The assumption that realistic AI-generated disaster imagery is inherently persuasive for climate action is challenged.
  • Adverse effects like reactance and reduced trust necessitate a cautious and informed approach to using generative AI in climate advocacy.
  • Future strategies should consider potential negative psychological impacts and transparency regarding AI's role.