Class 8: AI Ethics & Bias – Understanding Fairness in Technology
Learning Objectives:
- Recognize that AI can have biases
- Understand how bias enters AI systems
- Think critically about fairness in technology
- Explore ethical considerations in AI development
Key Topics:
- What is algorithmic bias?
- How bias gets into AI systems (biased training data, limited diversity)
- Real-world examples: Facial recognition errors, biased recommendation systems
- Fairness, accountability, and transparency in AI
- The importance of diverse data and inclusive design
- Ethics in AI: Privacy, consent, and responsible use
Activities:
- Case study analysis: Examining biased AI systems
- Re-curating datasets activity: Fixing bias through better data
- Ethical dilemma discussions: “What would you do?” scenarios
- Design challenge: Creating fair and inclusive AI applications
- Reflection journaling: Personal perspectives on AI ethics