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Found 2 papers, 1 papers with code
The Illusion of Competence: Evaluating the Effect of Explanations on Users' Mental Models of Visual Question Answering Systems
We examine how users perceive the limitations of an AI system when it encounters a task that it cannot perform perfectly and whether providing explanations alongside its answers aids users in constructing an appropriate mental model of the system's capabilities and limitations.
From Explainability to Explanation: Using a Dialogue Setting to Elicit Annotations with Justifications
Despite recent attempts in the field of explainable AI to go beyond black box prediction models, typically already the training data for supervised machine learning is collected in a manner that treats the annotator as a {``}black box{''}, the internal workings of which remains unobserved.
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