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When to Accept Automated Predictions and When to Defer to Human Judgment?

By Daniel Sikar and others
Ensuring the reliability and safety of automated decision-making is crucial. It is well-known that data distribution shifts in machine learning can produce unreliable outcomes. This paper proposes a new approach for measuring the reliability of predictions under distribution shifts. We analyze how the outputs of a trained neural network change... Show more
July 10, 2024
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When to Accept Automated Predictions and When to Defer to Human Judgment?
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