Ethical Considerations in AI Development

Building AI systems responsibly requires empathy, transparency, and oversight.

Fairness and Bias

Diverse datasets and frequent audits are essential to mitigate bias.

Transparency

Explain model predictions with interpretable techniques, documented data lineage, and accessible reporting.

Human-in-the-Loop

Involve subject-matter experts to approve critical AI decisions.

Resources

• Responsible AI documentation from leading cloud providers.
• Model cards and system cards for communicating system behavior.
• Community review boards for high-impact deployments.