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Algorithmic bias can perpetuate societal inequalities if not actively mitigated in ML systems.
- True
- False
Answer: True
Bias in training data or model design can lead to discriminatory outcomes. Mitigation: diverse datasets, fairness metrics, bias audits, human oversight. Critical for ethical AI deployment.