Models inherit our blind spots
An AI system learns from historical data—including its biases. Responsible AI is the practice of catching and correcting that before it affects real people.
Practical steps
- Check performance across groups, not just overall.
- Document data sources, assumptions, and limitations.
- Keep a human in the loop for high-stakes calls.
- Make decisions explainable to those affected.
Good ethics is good engineering
Fairness, transparency, and accountability aren't a compliance tax—they're what makes an AI system trustworthy enough to actually deploy.
