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3 cards from this section. Quick, good the night before a test.
What is bias in AI?
Think about the fairness of decisions made by AI.
Name one consequence of bias in AI systems.
Consider areas where consequences could be severe.
What is data bias?
Consider where the training information comes from.
True or False: Algorithmic bias can arise from the way AI algorithms process data.
Focus on how the algorithm impacts outputs.
Analyze a case study where bias in AI led to real-world consequences. What strategies could have been implemented to prevent this bias?
Think about major incidents reported in the media.
Develop a plan to evaluate the fairness of a healthcare AI system. List key metrics and strategies you would use.
Consider what variables influence healthcare outcomes.
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