An Expert System is designed to?

An Expert System is designed to replicate expert human decision-making, which means it aims to simulate the reasoning and decision-making abilities of a human expert in a specific field. This type of system utilizes knowledge bases that contain domain-specific information and inference rules that enable the system to analyze this information and arrive at conclusions or make recommendations similar to a human expert.

The key feature of Expert Systems is their ability to process inputs based on established rules and heuristics derived from expert knowledge. This capability allows organizations to leverage such systems in situations where human expertise might be scarce, costly, or unavailable, thus facilitating quicker and often more consistent decisions.

Other choices provided, such as generating new data inputs, monitoring AI compliance, and visualizing dataset transformations, pertain to different functions and applications of AI technologies. Generating new data inputs relates to data generation techniques rather than decision-making processes. Monitoring compliance focuses on regulatory adherence and ethical considerations in AI deployment, while visualizing dataset transformations deals with how data changes are represented, which does not directly relate to the core purpose of an Expert System. These distinctions help clarify the specialized function of Expert Systems within the broader landscape of AI applications.