Computing
Artificial Intelligence
Conceptual
9–11 yrs
Bias in AI Systems
人工智能系统中的偏见
Description
If training data is biased, AI will be biased; examples: facial recognition working better for some skin tones, translation assuming gender; where bias comes from and whether we can fix it
Mastery Evidence
- Explain what bias in AI means using a real-world example
- Describe how biased training data leads to biased AI results
- Suggest one way to reduce bias in an AI system (use more diverse data, test with different groups)
Assessment Prompt
Could your child explain why an AI trained mostly on photos of light-skinned faces might not work as well for people with darker skin?
