Course Overview
This self-paced course delves into the ethical dimensions of AI, covering privacy and data protection, bias identification and mitigation, accountability, transparency, and the development of robust AI policies to guide responsible deployment across industries.
Course Goals
Equip PhD scholars, academicians, and professionals with the knowledge and skills to formulate and enforce AI ethics policies, ensuring AI systems are fair, transparent, accountable, and compliant with legal standards.
Program Objectives
- Understand foundational ethical principles and their application to AI.
- Identify and mitigate bias in AI systems.
- Formulate AI policies prioritizing privacy and accountability.
- Analyze case studies to apply ethical frameworks effectively.
- Ensure AI solutions comply with global regulatory and ethical standards.
Program Structure
Module 1: Introduction to AI Ethics
- Ethical principles in AI
- Historical evolution of AI ethics
- Theoretical frameworks and applications
Module 2: Privacy and Data Protection
- Fundamentals of data privacy
- Legal frameworks & regulations
- Privacy-preserving AI techniques
Module 3: Bias in AI Systems
- Types and sources of bias
- Bias detection and mitigation methods
- Case studies and lessons learned
Module 4: Accountability and Transparency
- Defining accountability in AI
- Tools for transparency and auditability
- Frameworks for responsible AI development
Module 5: Ethical Policy Formulation
- Steps for creating AI ethics policies
- Integrating ethics into development lifecycles
- Best practices for implementation and enforcement
Module 6: Case Studies in Ethical AI
- Real-world ethical dilemmas and resolutions
- Success stories of ethical AI deployment
- Analysis of failures and key takeaways
Module 7: Regulatory Compliance & Standards
- Global AI regulations overview
- Ensuring legal and ethical compliance
- Emerging trends in AI governance
Module 8: Practical Applications & Tools
- Ethical AI toolkits and resources
- Hands-on projects and simulations
- Industry-specific ethical AI case studies
Participant Eligibility
Ideal for AI researchers, policymakers, ethics scholars, legal professionals, data scientists, and IT managers dedicated to promoting ethical AI practices and governance.
Learning Outcomes
- Develop comprehensive AI policies ensuring ethical standards.
- Implement fair, transparent, and accountable AI solutions.
- Conduct ethical risk assessments and policy audits.
- Lead initiatives in AI governance, compliance, and policy formulation.
