Module 1: Introduction to AI and Legal Landscape

• Legal Foundations and Basic principles of law
• Overview of Artificial Intelligence
  • Definition and types of AI
  • Historical development and current state

Module 2: Intellectual Property and AI

• Copyright and AI
  • Ownership of AI-generated content
  • Fair use and AI-generated works, and related Copyright issues
• Patents and AI
  • Can AI be an inventor?
  • Patentability of AI-generated inventions

Module 3: Privacy and Data Protection

• Data Privacy Laws
  • Privacy considerations in AI applications
  • GDPR, CCPA, and other global regulations
• Data Ownership and Consent
  • Who owns AI-generated data?
  • Informed consent in AI contexts
• Surveillance
  • AI in surveillance and privacy
  • Governmental use of AI versus privacy 

Module 4: Liability and Accountability

• Legal Responsibility
  • Attribution of liability in AI accidents
  • Legal personhood for AI entities
• Tort Law and AI
  • Negligence and AI
  • Strict liability in AI cases

Module 5: Regulation and Compliance

• National and International Regulation
  • Overview of AI regulations worldwide
  • Challenges in harmonizing global AI regulations
• AI in Specific Sectors
  • Healthcare, finance, transportation, etc.
  • Sector-specific regulatory challenges

Module 6: Governance and Policy-making

• Ethical Frameworks for AI
  • Development and implementation of ethical guidelines
  • Challenges in enforcing ethical standards
• Governmental Policies
  • National AI strategies
  • Regulatory sandboxes and innovation hubs
  • AI and democracy
• AI and the criminal justice system

Module 7: Social Implications

• Employment and Workforce
  • Impact of AI on employment
  • Reskilling and upskilling initiatives
• Equity and Access
  • Bridging the digital divide
  • Ensuring equitable access to AI technologies
• Education
  • Impact of AI on education
  • Legal implications of AI in education
• AI versus Humans
  • AI systems legal personhood
  • AI liability versus Human Liability 

Module 8: Future Trends and Emerging Issues

• Explainability and Transparency
  • Challenges in understanding AI decision-making
  • Importance of transparency in AI systems
• Human Rights and AI
  • Impact on freedom of expression, privacy, etc.
  • Ensuring AI respects fundamental human rights

Module 9: Case Studies and Practical Applications

• Real-world Examples
  • High-profile legal cases related to AI
  • Successful and problematic implementations
• Interactive Discussions and Debates
  • Engaging students in analyzing and discussing AI legal issues
  • Mock trials and legal simulations

Module 10: Future Directions and Student Projects

• Emerging Technologies
  • Quantum computing, neurotechnology, etc.
  • Legal and policy implications of future AI advancements
• Capstone Projects
  • Students develop and present projects on a specific AI law and policy topic
  • Integration of multidisciplinary approaches