1.0Generative Imageryhttps://gi.uni-bremen.degimageshttps://gi.uni-bremen.de/?author=1Generative Images - Generative Imageryrich600338<blockquote class="wp-embedded-content" data-secret="oonfj8AxJB"><a href="https://gi.uni-bremen.de/">Generative Images</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://gi.uni-bremen.de/?embed=true#?secret=oonfj8AxJB" width="600" height="338" title="„Generative Images“ – Generative Imagery" data-secret="oonfj8AxJB" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script type="text/javascript">
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Societal discourse about the benefits, risks, and challenges of artificial intelligence (AI) is in fullswing. To date much of the debate has focused on text-to-text generators such as Chat-GPT,Bing, or Bard (for a recent overview see Sachs-Hombach et al. 2023). Yet, rapid AI developmentis also fundamentally changing visual communication: With Stable Diffusion, Dall-E orMidjourney, powerful AI generators of images and image sequences have long been available whose output is impressive in terms of diversity, richness of detail and image complexity. AI-generated images have long been used in a variety of media, social, and political contexts -even for strategic persuasion and political propaganda - and without the generative origin beingobvious to users or being disclosed.Generative images - generative imageries (GI) - thus offer enormous potential tofundamentally change the production, use, reception and handling of images. At the same time,little light has been shed on what it actually means for our understanding of imagery whenimages are increasingly produced generatively. Does this mean the “end of truth” as theestablished German news magazine Der Spiegel headlined in July 2023 emphasizing thechallenges of generative imagery?