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Problematic Datasets

AI models are often trained on datasets that don’t fully represent the diversity of the human population. This is a significant issue because biased or incomplete datasets lead to AI systems that mirror these same biases in their performance. Learn about five examples of problematic datasets and the potential risks they pose to individuals. This video is part of the online learning unit "Fairer Algorithms", which was created as part of the "Competencies for the (digital) future" (KDZ) program. Further information on the KDZ program and other modules can be found at: https://unibe.ch/kdz Module "Fairer Algorithms": https://www.unibe.ch/studies/programs...