GMU:Hallucinating computers and dreaming non-machines/Lina Louise Wolff: Difference between revisions

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 ==Background information==
-We use the research we did for our last project as inspiration and information to create multiple layers, which communicate the gaps which lead to inequality and a lack of knowledge when it comes to female health.
+The work explores how the lack of female representation in research and clinical trials has led to disproportionate adverse drug reactions in women. These effects are the result of healthcare systems historically designed around male bodies, often treating them as the default in diagnostics, treatment, and pharmaceutical development, showing that health systems are taking better care of male bodies then of any others. The unequal treatment gets visible through gaps, most common known as the gender data gap.
+In a previous
+The AI  functions by analyzing visual input through multiple neural network layers. With each layer, specific features are exaggerated, leading to a progressively surreal image. When the algorithm encounters ambiguity, it begins to “hallucinate”—projecting its own learned patterns onto the input.
 ==Idea/Concept==
-Analoge reconstructing Google DeepDream .
+The installation reinterprets in an analoge way how image dreaming AIs, like Google’s DeepDream, start to hallucinate and dream .
 The Image AI Creator DeepDream from google uses multiple layers to create a surreal image. With every layer the image gets more obvious.