Claire, the AI Quality Assurance Manager at MDFT Pro, is developing robust data handling procedures for the company’s machine learning systems that process student information and course data. MDFT Pro, a well-known training agency, collects data from various sources including online enrollment forms, mobile applications, and third-party integration systems, which sometimes results in incomplete records, missing values, or unusual data entries. Claire needs to ensure that the AI systems can handle these data quality issues gracefully without system failures, incorrect predictions, or unreliable outputs that could affect student experiences or business decisions.
Which responsible AI principle addresses the requirement for AI systems to properly handle unusual or missing values in input data?
Choose the correct answer from the options below.
Explanations for each answer: