Microsoft Azure AI Fundamentals (AI-900) Practice Exam

Which principle is primarily concerned with ensuring fairness in AI operations?

1. Inclusiveness

2. Accountability

3. Fairness

4. Transparency

The correct answer is: Fairness

Fairness in AI operations is a crucial principle that seeks to ensure that AI systems do not exhibit bias or discrimination against individuals or groups. This principle emphasizes the importance of developing algorithms and models that provide equitable treatment and outcomes, regardless of variables such as race, gender, or socio-economic status. The focus on fairness involves evaluating how data is used, ensuring representative data sets, and implementing measures that reduce bias throughout the AI lifecycle. When AI systems are fair, they contribute to building trust among users and society at large, leading to more responsible and ethical use of AI technologies. While inclusiveness, accountability, and transparency are also important principles in the design and deployment of AI systems, they serve different roles. Inclusiveness focuses on ensuring diverse perspectives are considered; accountability is about holding stakeholders responsible for AI outcomes; and transparency involves making the workings of AI systems clear and understandable. Fairness specifically targets the mitigation of bias and the equitable treatment of individuals, making it the core principle focused on achieving fair AI operations.