AI Ethics and Bias Flashcards
6 cards from real Artificial Intelligence practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 AI Ethics and Bias flashcards as text
What is 'algorithmic bias' in AI systems?
Answer: Systematic errors in AI outputs that unfairly favor or disadvantage certain groups
Algorithmic bias occurs when AI systems produce systematically unfair outcomes, often reflecting biases present in training data.
What does 'fairness' in AI typically require?
Answer: Equitable treatment and outcomes for individuals across demographic groups
AI fairness aims to ensure that model decisions do not systematically disadvantage individuals based on protected attributes.
What is 'explainability' (or interpretability) in AI?
Answer: The degree to which humans can understand and trace how an AI makes decisions
Explainability refers to how transparently an AI system's reasoning can be understood by humans.
What is 'data privacy' in the context of AI model training?
Answer: Ensuring that personal data used in training is handled, stored, and used in accordance with privacy laws
Data privacy in AI means protecting individuals' personal information used during model training from unauthorized access or misuse.
What is the 'right to explanation' in AI regulation?
Answer: The right of individuals to receive a meaningful explanation of automated decisions affecting them
The right to explanation allows people affected by automated decisions to understand the reasoning behind them.
What is 'model transparency' in responsible AI?
Answer: Openly documenting how a model works, what data it was trained on, and its limitations
Model transparency involves disclosing key information about the model's design, training data, and performance to enable accountability.