AI+ Ethics (AIET) – Outline

Detailed Course Outline

Module 1: Overview of AI Ethics & Societal Impact

• 1.1 Introduction to Ethical Considerations in AI
• 1.2 Understanding The Societal Impact of AI Technologies
• 1.3 Strategies for Conducting Social and Ethical Impact Assessments

Module 2: Bias and Fairness in AI

• 2.1 Exploration of Biases in Data and Algorithms
• 2.2 Strategies for Mitigating Bias and Ensuring Fairness in AI Systems

Module 3: Transparency and Explainable AI

• 3.1 Importance of Transparent AI Systems
• 3.2 Techniques for Explaining AI Models to Diverse Stakeholders
• 3.3 Guided Projects on Designing and Analysis of AI Systems with Ethical Considerations

Module 4: Privacy and Security Issues in AI

• 4.1 Examination of Privacy Concerns Related to AI
• 4.2 Strategies for Ensuring the Security of AI Systems and Data

Module 5: Accountability and Responsibility

• 5.1 Concepts of Accountability in AI Development and Deployment
• 5.2 Responsibilities of AI Practitioners and Organizations

Module 6: Legal and Regulatory Issues

• 6.1 Overview of Relevant Laws and Regulations Pertaining to AI
• 6.2 Understanding the Global Regulatory Issues for AI Technologies
• 6.3 Case Studies: GDPR Compliance
• 6.4 Legal Compliance of AI Tools

Module 7: Ethical Decision-Making Frameworks

• 7.1 Introduction to Frameworks for Making Ethical Decisions in AI
• 7.2 Case Studies and Applications of Ethical Decision-Making
• 7.3 Use of Simulation Platforms in Ethical Decision-Making

Module 8: AI Governance & Best Practices

• 8.1 Principles and Functions of International AI Governance
• 8.2 Best Practices for Integrating AI Ethics into Organizational Policies
• 8.3 Case Studies on AI Governance

Module 9: Global AI Ethics Standards

• 9.1 Explore Standards like IEEE’s Ethically Aligned Design
• 9.2 Comparative Case Studies on Standard Implementations
• 9.3 Tools for Evaluating AI Systems Against Global Standards