Microsoft Azure AI Fundamentals (AI-900) Practice Exam

When developing an AI system for self-driving cars, which principle should be applied to ensure consistent operation during unexpected circumstances?

1. Transparency

2. Reliability and safety

3. Inclusiveness

4. Accountability

The correct answer is: Reliability and safety

In the context of developing AI systems for self-driving cars, applying the principle of reliability and safety is crucial to ensure that the vehicle can react appropriately to unexpected circumstances. This principle focuses on creating a system that is dependable under various conditions, including those that are unforeseen or potentially hazardous. Reliability ensures that the AI system performs consistently, regardless of variations in the environment, such as adverse weather conditions, sudden obstacles, or erratic behavior from other road users. Safety is paramount, as self-driving cars must not only operate correctly under normal conditions but also manage risks effectively to protect passengers, pedestrians, and other road users. This principle involves rigorous testing, validation, and adherence to safety standards throughout the development process. It ensures that the AI can make accurate decisions even in situations it has not previously encountered, thereby instilling confidence in its operation. While the other principles, such as transparency, inclusiveness, and accountability, are also important in the broader context of ethical AI and its implementation, they are not as directly focused on the critical operational requirements necessary for self-driving technology to function effectively and safely in unpredictable scenarios. Reliability and safety take precedence in this specific use case, making it the most relevant principle for this question.