Ethics, Safety, and Bias

Neural nets learn what they see. If training data is biased, the model may be biased. Key ideas:

• Dataset curation and evaluation on diverse slices.
• Explainability tools (feature attributions, probes) to audit behavior.
• Safety: avoid harmful outputs; consider rate limits, human review, domain constraints.