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3 cards from this section. Quick, good the night before a test.
What is bias in AI models?
Think about how AI might make errors based on who or what it's trained on.
Why is data privacy important in AI?
Consider what could happen if personal data is shared without consent.
What is a consequence of bias in AI models?
Think about how the training data influences the model's decisions.
True or False: Overfitting occurs when a model learns to generalize too well to new data.
Relate this to the importance of using diverse datasets.
You have an AI that performs wonderfully in trials but fails in real-world tests. Identify the possible ethical issue and solutions.
What happens when a model learns too much from its training data?
Design a protocol for handling personal images in an AI project to ensure privacy and ethical standards.
Think about what measures will build trust with users.
4 more questions in this section. Enroll free to practise them all.
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