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3 cards from this section. Quick, good the night before a test.
Define bias in AI models.
Think about how data influences AI outcomes.
What is data privacy?
Consider what it means to keep information safe.
What is bias in AI?
Consider how training data impacts fairness.
True or False: Overfitting affects an AI model's performance on training data positively.
Think about the concept of training vs. new data.
Create a plan for an ethical AI project that incorporates diverse datasets. Outline the steps you would take to ensure fairness and privacy.
Think about varying sources and diverse perspectives.
Design a small public awareness campaign on the dangers of overfitting in AI, targeting a lay audience. What would your key messages be?
Consider real-world implications to make it relatable.
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