Final answer:
The inability to understand the decision-making process of complex models is referred to as the Black box problem, common in AI and machine learning.
Step-by-step explanation:
As models become more complex, researchers are unable to reason why the decisions are being made. This is called the Black box problem. The term 'black box' refers to a situation where the internal workings of a model, particularly in artificial intelligence and machine learning, are not visible or understandable to the observer, despite the model producing results or decisions. It raises concerns regarding transparency and trustworthiness because it becomes difficult to explain how a model derived at a particular conclusion or prediction.