Day 1: Introduction to AI in Law

1. Overview of AI Technologies in Law

• Definition and types of AI: Machine Learning, Natural Language Processing, Expert Systems
• Historical development of AI in legal contexts
• Key AI technologies used in legal practice: document review, legal research, predictive analytics

2. Applications of AI in Legal Research

• AI-powered legal research platforms (e.g., ROSS Intelligence, Lexis Advance)
• Natural Language processing for case law analysis
• Automated brief analysis and citation checking
• Limitations and potential biases in AI-assisted legal research

3. AI in Document Review and Analysis

• Machine learning algorithms for e-discovery
• Predictive coding and technology-assisted review (TAR)
• Contract analysis and due diligence automation
• Case studies: Efficiency gains in large-scale litigation

Day 2: Ethical Considerations and Practical Applications

1. Ethical Implications of AI in Legal Practice

• Professional responsibility and AI use
• Maintaining attorney competence with AI tools
• Confidentiality and data security concerns
• Transparency and explain ability of AI-generated results

2. Bias in AI Systems and Impact on Legal Decisions

• Types of bias in AI: selection bias, algorithmic bias, outcome bias
• Case studies of AI bias in legal contexts (e.g., COMPAS recidivism algorithm)
• Strategies for detecting and mitigating bias in legal AI tools

3. Data Privacy Concerns in AI-Driven Legal Tools

• Data protection regulations relevant to AI in law (e.g., GDPR, CCPA)
• Client data handling and AI training datasets
• Ethical considerations in using client data for AI model improvement

4. Hands-on Session with AI-Powered Legal Research Tools

• Introduction to popular AI legal research platforms
• Demonstration of advanced search techniques and analytics features
• Practical exercise: Conducting AI-assisted legal research on a complex legal issue
• Critical evaluation of AI-generated research results