Künstliche Intelligenz: Bild und Bias

Image-generative AI produces distorted, often stereotypical images of reality. Why is this the case and how can it be counteracted? In the presentation, the functionalities of Generative Adversarial Networks and diffusion models are presented with advantages and problems in the use, bias in existing models is shown and strategies for avoiding bias are discussed. The focus is on the generation of gender-equitable image material, whereby intersectional aspects are also taken into account. The presentation accompanies episode 13 of the podcast AI in Teaching on bias in image-generative AI: https://www.youtube.com/playlist?list=PLLmr_XhQwwKNAuJLA8bpNUHv0QiGvvs1v

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Intersektionaler Bias, Bias in der Bilderzeugung mit generativer KI, intersectional bias, gender bias, Bias in image generation with generative AI, Genderbias

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https://open.uni-marburg.de/handle/10.17192/es.2025.0034

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Künstliche Intelligenz: Bild und Bias

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