What You Need to Know Before
You Start
Starts 6 June 2025 12:49
Ends 6 June 2025
00
days
00
hours
00
minutes
00
seconds
1 hour 4 minutes
Optional upgrade avallable
Not Specified
Progress at your own speed
Free Video
Optional upgrade avallable
Overview
Explore how AI can be applied to legal reasoning with a focus on trustworthiness, presented by Ruzica Piskac from Yale University at the Simons Institute.
Syllabus
- Introduction to AI in Legal Reasoning
- Foundations of Trustworthy AI
- AI Techniques for Legal Analysis
- Building Explainable AI Systems
- Ensuring Fairness in AI Legal Systems
- Security and Privacy in Legal AI
- Trust and Transparency in AI
- Legislative and Regulatory Perspectives
- Case Studies and Applications
- Ethical Implications and Considerations
- Future of AI in Legal Reasoning
- Conclusion and Course Wrap-up
Overview of AI's role in legal contexts
Historical development and key milestones
Definitions and principles of trustworthy AI
Importance of ethics and accountability
Natural Language Processing (NLP) in legal documents
Machine learning models for legal predictions
Techniques for interpreting AI decisions
Case studies on explainable AI in law
Identifying and mitigating bias
Frameworks for fairness evaluation
Data protection and privacy concerns
Strategies for secure AI deployment
Building transparent AI infrastructures
Tools for auditing AI systems
Existing regulations affecting AI in law
Potential future developments in legal AI regulation
Real-world examples of AI in legal reasoning
Successes and challenges in implementation
Balancing innovation with societal impact
Discussion on ethical dilemmas in AI deployment
Emerging trends and technologies
Vision for the future of AI in legal systems
Key takeaways and reflections
Open discussion on course content and future learning paths
Subjects
Computer Science