Responsible AI Flashcards
6 cards from real Microsoft Azure AI Fundamentals practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Responsible AI flashcards as text
What is AI bias and why is it a concern in the context of Responsible AI?
Answer: AI bias occurs when models produce skewed or unfair results due to unrepresentative training data or flawed design
AI bias arises when training data or model design reflects societal inequities, causing models to produce unfair or discriminatory outcomes for certain groups.
Which Azure tool helps teams detect and mitigate fairness issues in machine learning models?
Answer: Fairlearn (integrated with Azure Machine Learning)
Fairlearn is an open-source toolkit integrated with Azure Machine Learning that helps assess and mitigate fairness-related harms in machine learning models.
In the context of Responsible AI, what is a 'human in the loop'?
Answer: A person involved in reviewing, overriding, or approving AI decisions to ensure oversight
Human in the loop refers to a design approach where humans review and can override AI decisions, ensuring meaningful oversight especially in high-stakes scenarios.
What does 'model explainability' mean in Responsible AI practice?
Answer: The capacity to understand and communicate why a model made a specific prediction
Model explainability refers to techniques that help stakeholders understand why an AI model produced a particular output or decision.
Which practice helps ensure AI systems respect user data under the Privacy & Security principle?
Answer: Implementing data minimization, encryption, and access controls on AI training and inference pipelines
Privacy & Security best practices include collecting only necessary data, anonymizing training datasets, encrypting data in transit and at rest, and restricting access to sensitive information.
What is the purpose of a 'model card' in Responsible AI documentation?
Answer: A structured document that describes a model's intended use, performance metrics, limitations, and ethical considerations
A model card is a transparency artifact that summarizes what a model does, how it performs across different groups, its limitations, and the contexts in which it should or should not be used.