Question

What is the black box problem?

A: The problem created when researchers don't create accurate attributes for a model
B: When a model cannot accurately judge shape or color of objects due to missing data
C: The issue of not having enough data to accurately train a model
D: When a model is deployed, but researchers are unable to figure out why it's making decisions

Answer 1

The black box problem refers to the situation when a deployed model's decision-making process is not transparent or easily understood.

Step-by-step explanation:

The black box problem refers to the situation when a model is deployed, but researchers are unable to figure out why it's making decisions. It is called a 'black box' because the inner workings of the model are not transparent or easily understandable. This lack of transparency can be a challenge when trying to trust and interpret the outputs of the model.