Responsible AI: Principles, Practices, and Applications

Overview

Unlock the potential of Artificial Intelligence while ensuring ethical integrity and societal benefit with our comprehensive course, "Responsible AI:

Principles, Practices, and Applications."

Syllabus

• Introduction to Responsible AI
Overview of AI and its societal impact
Importance of ethics in AI development and deployment
• Principles of Responsible AI
Fairness and Bias Mitigation
Transparency and Explainability
Privacy and Data Protection
Accountability and Governance
• Ethical Frameworks and Guidelines
Review of existing ethical guidelines (e.g., IEEE, EU, AI4People)
Legal and regulatory considerations
• Bias and Fairness in AI
Identifying and quantifying bias in AI systems
Techniques for mitigating bias
Case studies of bias in AI applications
• Transparency and Explainability
Importance of model interpretability
Techniques for improving explainability (e.g., LIME, SHAP)
Balancing performance and transparency
• Privacy and Data Protection in AI
Handling sensitive data and ensuring confidentiality
Privacy-preserving techniques (e.g., differential privacy, federated learning)
Data governance best practices
• Accountability and Governance in AI Systems
Establishing responsibility in AI development and deployment
Building ethical AI governance frameworks
Roles of stakeholders (developers, policymakers, and users)
• Responsible AI Practices
Integrating ethical considerations throughout the AI lifecycle
Developing inclusive AI systems
Continuous monitoring and feedback mechanisms
• Case Studies and Applications
Review of responsible AI applications across industries
Analysis of ethical considerations and outcomes
Lessons learned and best practices
• Project: Designing a Responsible AI System
Definition of project scope and objectives
Identifying potential ethical challenges
Implementing and presenting the responsible AI solution
• Future Directions in Responsible AI
Emerging trends and technologies
Ongoing challenges and research areas
The evolving role of AI in society

Taught by

Stuart Wesselby

Subjects

Data Science