What does accuracy measure in an AI system?

Accuracy in an AI system specifically measures the degree of correct task performance. It quantifies how well the AI system's outputs match the expected or desired results when processing data. By focusing on correctness, accuracy serves as a fundamental metric to evaluate the effectiveness of the AI system in achieving its objectives, such as identifying images, making predictions, or classifying data.

In the context of AI and machine learning, accuracy is calculated as the ratio of correctly predicted instances to the total instances evaluated. A higher accuracy percentage indicates that the model is performing well in correctly understanding or predicting outcomes based on the provided data.

The other options relate to different aspects of an AI system's functionality but do not pertain to accuracy specifically. Speed of data processing relates to the performance and efficiency of the system. The complexity of the model refers to how complex the algorithms and data structures are, which affects performance, but not necessarily accuracy directly. User satisfaction rate considers the end user's experience and opinions, which is important for usability but does not measure the correctness of task performance in a technical sense. Thus, option B directly aligns with the definition of accuracy in AI systems.