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Bias in AI Systems

CONCEPTUAL
Computing›Artificial Intelligence|Ages 9—11|ID: mt__BbOjiY5A5

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 [child] explain why an AI trained mostly on photos of light-skinned faces might not work as well for people with darker skin?”

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