Developers of many new AI solutions produce statistics showing that the tools make critical decisions with greater accuracy and efficiency than humans. But managers tasked with evaluating these applications need to peel back the layers of developers' performance claims and focus on the ground truth used to train and validate the AI tool. This article explains what ground truth is, how to identify it for a given tool, and how to understand the implications for tool quality.

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