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A prerequisite knowledge graph of 1590 learning concepts across 8subjects. Track what you've mastered and see exactly what you're ready to learn next — the topics whose prerequisites you've already met. Built on the Marble Open Skill Taxonomy.

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Bias in AI Systems

Computing · Artificial Intelligence · conceptual

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

What mastery looks like

  • 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)

Check your understanding

Could Bias in AI Systems explain why an AI trained mostly on photos of light-skinned faces might not work as well for people with darker skin?