Why is interpretability important in AI?

Why is interpretability important in AI?

Interpretability in AI is crucial because it helps users understand how decisions are made, ensuring trust and accountability.

Can you give me examples of where lack of interpretability caused issues?

Sure! One example is in healthcare, where opaque AI models led to misdiagnoses, affecting patient outcomes.

How can we improve the interpretability of AI models?

We can improve interpretability by using simpler models, providing visualizations, and implementing techniques like LIME or SHAP.

What are the trade-offs between accuracy and interpretability?

Often, more complex models yield higher accuracy but lower interpretability. Balancing both is key depending on the application.

Are there regulations regarding AI interpretability?

Yes, some regions are starting to implement regulations that require AI systems to be interpretable, especially in critical sectors.