AI Ethics and Bias
Understand ethical considerations in AI.
Build responsible AI.
Why Ethics Matter
AI affects real people's lives: - Loan approvals - Job applications - Medical diagnoses - Criminal justice
AI Bias
AI learns from data. If data has bias, AI will too!
Example of Bias
Hiring AI trained on past hires: - If company mostly hired men - AI learns: men = better candidates - AI discriminates against women
**This is wrong!**
Sources of Bias
1. **Historical data**: Past discrimination 2. **Incomplete data**: Missing groups 3. **Biased labels**: Human prejudice
Real Case
Amazon's hiring AI showed bias against women. They stopped using it!
Fairness in AI
AI should treat everyone fairly: - All races equally - All genders equally - All ages equally
Privacy Concerns
AI often uses personal data: - Face recognition - Location tracking - Browsing history
**Balance**: Useful AI vs Privacy protection
Building Fair AI
- Use diverse data - Test for bias - Include diverse teams - Be transparent
Remember
- AI can be biased - Check for fairness - Protect user privacy - Build responsible AI