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5 cards from this section. Quick, good the night before a test.
What does explainability in AI mean?
Think about what makes AI decisions trustworthy.
Name one consequence of data privacy violations in AI.
Consider the implications for users.
What does explainability in AI primarily foster?
Consider the importance of understanding AI decisions.
True or False: Robustness refers to AI systems' ability to withstand adversarial attacks.
Think of a system that can handle unexpected challenges.
Propose a robust AI model framework that addresses both explainability and fairness.
Think about model types that are inherently more understandable.
Analyze a recent AI system deployment that faced backlash due to privacy issues. What lessons can be learned?
Review incidents where user data was compromised and how they could have been avoided.
5 more questions in this section. Enroll free to practise them all.
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