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Kassel University, Kassel, Germany
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Students learned that annotation disagreement is a valuable insight into the complexity of data interpretation, not merely a flaw in labeling.
Algorithmic decisions about humans can now be audited for "Representation Fidelity" by checking if they align with self-reported descriptions, revealing potential biases and inaccuracies.
