Trustworthy AI for Legal Reasoning

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
Overview of AI's role in legal contexts
Historical development and key milestones
• Foundations of Trustworthy AI
Definitions and principles of trustworthy AI
Importance of ethics and accountability
• AI Techniques for Legal Analysis
Natural Language Processing (NLP) in legal documents
Machine learning models for legal predictions
• Building Explainable AI Systems
Techniques for interpreting AI decisions
Case studies on explainable AI in law
• Ensuring Fairness in AI Legal Systems
Identifying and mitigating bias
Frameworks for fairness evaluation
• Security and Privacy in Legal AI
Data protection and privacy concerns
Strategies for secure AI deployment
• Trust and Transparency in AI
Building transparent AI infrastructures
Tools for auditing AI systems
• Legislative and Regulatory Perspectives
Existing regulations affecting AI in law
Potential future developments in legal AI regulation
• Case Studies and Applications
Real-world examples of AI in legal reasoning
Successes and challenges in implementation
• Ethical Implications and Considerations
Balancing innovation with societal impact
Discussion on ethical dilemmas in AI deployment
• Future of AI in Legal Reasoning
Emerging trends and technologies
Vision for the future of AI in legal systems
• Conclusion and Course Wrap-up
Key takeaways and reflections
Open discussion on course content and future learning paths

Subjects

Computer Science