More accurate uncertainty estimates could help users decide about how and when to use and trust AI models in the real world.

When to trust an AI model


More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world

This story was originally published by MIT News.

Because machine-learning models can give false predictions, researchers often equip them with the ability to tell a user how confident they are about a certain decision. This is especially important in high-stake settings, such as when models are used to help identify disease in medical images or filter job applications.

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