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