Why is model interpretability important in AI?
Model interpretability is crucial because it helps users understand how AI makes decisions, ensuring transparency and trust.
Can you give me an example of a situation where interpretability is necessary?
Sure! In healthcare, if an AI predicts a diagnosis, doctors need to understand the reasoning behind it to make informed decisions.
What are the risks of using black-box models?
Black-box models can lead to biased or incorrect decisions without clear explanations, which can harm users and erode trust.
How can we improve model interpretability?
We can improve interpretability by using simpler models, visualization tools, and techniques like LIME or SHAP to explain predictions.
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