What is involved in Data Analysis and Auditing to detect bias in AI systems?

Group of answer choices

Data Analysis and Auditing focuses on verifying that the AI system uses only a single data source to avoid any inconsistencies in the results.

Data Analysis and Auditing focuses on improving the performance of AI systems by reducing the size of training data without assessing its fairness.

Data Analysis and Auditing involves manually tweaking the AI system's outcomes to avoid undesirable results, without analyzing the underlying data.

Data Analysis and Auditing is used solely to remove irrelevant features from the dataset and optimize the model's speed, without concern for fairness.

Data Analysis and Auditing involves examining the training data, performing feature analysis, and checking for historical bias in the data.