Microsoft Azure AI Fundamentals (AI-900) Practice Exam

What is the primary principle of responsible AI that emphasizes the need for AI systems to be free from biases?

1. Transparency

2. Fairness

3. Accountability

4. Inclusiveness

The correct answer is: Fairness

The principle of responsible AI that emphasizes the need for AI systems to be free from biases is fairness. Fairness in AI means ensuring that the algorithms and models do not produce biased outcomes or discrimination against individuals based on their characteristics, such as race, gender, age, or other factors. This principle is critical because biased AI systems can perpetuate and amplify existing societal injustices, leading to unfair treatment of certain groups. Fairness requires that data used to train AI systems is representative of diverse populations and that the decision-making processes of these systems are designed to treat all individuals equally and justly. By focusing on fairness, organizations can work towards creating AI technologies that are ethical and serve all members of society equitably. In contrast, the other principles mentioned—transparency, accountability, and inclusiveness—also play important roles in responsible AI but are not specifically centered on addressing bias. Transparency involves making the workings of AI systems clear and understandable, accountability refers to ensuring that there are mechanisms to hold organizations responsible for the outcomes produced by AI, and inclusiveness pertains to the engagement of diverse stakeholders in the development and deployment of AI systems. Each of these principles supports the overall aim of creating ethical AI, but fairness is the specific principle that targets the elimination of