Microsoft Azure AI Fundamentals (AI-900) Practice Exam

What principle ensures that an AI system refrains from making predictions when faced with unusual or missing values?

1. Transparency and Explainability

2. Fairness and Accountability

3. Reliability and Safety

4. Privacy and Security

The correct answer is: Reliability and Safety

The principle that ensures an AI system refrains from making predictions when faced with unusual or missing values is rooted in the concepts of reliability and safety. This principle emphasizes the importance of an AI system maintaining a high level of performance and dependability, even in the face of incomplete or unexpected input data. Reliability focuses on the system's ability to function correctly and consistently under various conditions. When an AI system encounters unusual data or missing values, it may lead to inaccurate predictions or harmful decisions. By adhering to the principles of reliability and safety, a well-designed AI system is programmed to recognize when data inputs do not meet certain criteria or when it falls outside of the 'norm' established during training. In such cases, the system can appropriately choose not to make a prediction or decision, thus avoiding potential risks and ensuring user safety. In the context of AI applications, this principle is crucial because it prevents the system from acting on uncertain or flawed data, which could result in unintended consequences. By ensuring reliability and safety, AI systems can enhance user trust and promote responsible usage of technology.