What are some examples of opaque models in AI?

What are some examples of opaque models in AI?

Opaque models in AI are those whose internal workings are not easily interpretable. Examples include deep neural networks, ensemble methods like random forests, and certain types of support vector machines.

Why are opaque models used if they are hard to interpret?

Opaque models are often used because they can achieve higher accuracy and performance on complex tasks compared to more interpretable models.

Can you give me an example of a situation where an opaque model might be preferred?

Sure! In medical diagnosis, an opaque model might be preferred for analyzing complex patterns in patient data to predict diseases, even if we can't fully understand how it arrives at its conclusions.

What are the risks of using opaque models?

The risks include lack of transparency, potential biases in decision-making, and challenges in accountability, especially in critical areas like healthcare or finance.