Generated by claude-sonnet-4-6 · 2026-06-21 03:19 · grounding rag
Model Answer
(C) It can result in unfair and discriminatory outcomes.
AI bias occurs when training data or algorithms reflect existing prejudices, leading to unfair and discriminatory outcomes against certain groups.
Explanation
- Option (A) is incorrect — bias is not always negative; sometimes it simplifies models usefully, but harmful bias is the concern.
- Option (B) confuses bias with overfitting — two separate concepts.
- Option (D) is incorrect — machines reflect human-introduced bias; they do not generate independent biases of their own.
- The case study in the chapter clearly illustrates how an algorithm trained on skewed healthcare data led to discriminatory outcomes for patients from the western region, confirming (C) as correct.