16.4 Ethical AI Design Patterns

In this section

• Bias Detection and Mitigation Pattern in AI Systems
  Explore the Bias Detection and Mitigation Pattern in AI, focusing on understanding, detecting, and addressing bias in AI systems to ensure fairness and ethical use.
• Privacy-Preserving Machine Learning: Ensuring Data Privacy in AI Models
  Explore the techniques and principles of privacy-preserving machine learning, including federated learning, differential privacy, and homomorphic encryption, to protect individual data privacy in AI models.
• Ethical Decision-Making Framework Pattern in AI Design
  Explore the integration of ethical considerations into AI decision-making processes with a comprehensive framework aligning with organizational values and stakeholder impact.
• Human-in-the-Loop Pattern in AI Systems: Enhancing Accuracy and Ethical Oversight
  Explore the Human-in-the-Loop (HITL) pattern in AI systems, focusing on its benefits, implementation strategies, and ethical considerations. Learn how HITL enhances model accuracy and adaptability with practical examples and design insights.