What are some real-world examples of validation in AI?

What are some real-world examples of validation in AI?

Validation in AI refers to the process of ensuring that a model performs well on unseen data. Some real-world examples include validating a speech recognition system by testing it with diverse accents, or validating a medical diagnosis AI by comparing its predictions against expert evaluations.

Can you give me a specific example in healthcare?

Sure! One example is the use of AI in radiology. AI models are validated by comparing their ability to detect tumors in medical images against the diagnoses made by radiologists. This helps ensure the AI's accuracy and reliability in clinical settings.

What about in finance?

In finance, AI models used for credit scoring are validated by assessing their predictions against actual loan performance. This helps to ensure that the model accurately predicts the likelihood of a borrower defaulting on a loan.

How do companies typically conduct these validations?

Companies often use techniques like cross-validation, where they split their data into training and testing sets, and they may also conduct A/B testing in real-world scenarios to compare the performance of the AI model against existing methods.