Full Abstract Machine learning technology has become ubiquitous, but, unfortunately, often exhibits bias. As a consequence, disparate stakeholders need to interact with and make informed decisions about using machine learning models in everyday systems. Visualization technology can support stakeholders in understanding and evaluating trade-offs between, for example, accuracy and fairness of models. This paper aims … Continue reading "My Model is Unfair, Do People Even Care? Visual Design Affects Trust and Perceived Bias in Machine Learning "
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