AI & Technology in Legal Practice

Navigate AI adoption responsibly. Covers AI capabilities in legal research, competence and supervision duties, confidentiality with AI vendors, predictive coding in litigation, algorithmic bias, and the future of legal practice.

6 Units

Early Units (Foundation)

Building Skills

Advanced Concepts

Capstone/Synthesis

AI Capabilities and Limitations in Legal Work

Examines the current state of AI in legal work, focusing on proven applications in research, document review, and contract analysis, while identifying critical limitations that affect professional responsibility.

20 minutes

Competence and Supervision Duties with AI Tools

Analyzes the competence and supervision requirements under Model Rules 1.1, 5.1, and 5.3 as applied to AI use in law practice, including verification protocols and accountability frameworks.

20 minutes

Confidentiality When Using AI: Data Processing and Privilege

Examines the confidentiality and privilege risks when client information is processed by AI systems, including vendor data handling, waiver analysis, and client consent requirements under Model Rule 1.6.

20 minutes

AI in Litigation and E-Discovery: TAR, Validation, and Daubert

Examines the use of AI in litigation, focusing on technology-assisted review protocols, court-ordered validation requirements, and the admissibility standards for AI-generated evidence under Daubert and Federal Rule of Evidence 702.

20 minutes

Bias and Fairness in AI Systems

Examines algorithmic bias in AI systems, focusing on civil rights implications, disparate impact liability, and the ethical duties of attorneys who use or challenge biased AI tools in employment, lending, criminal justice, and other contexts.

20 minutes

The Future of Legal Practice with AI

Examines the structural changes AI will bring to legal practice, including the displacement of routine tasks, the evolution of billing models, changing competency requirements, and the potential for AI to improve access to justice.

20 minutes

Learning Progression

This course is designed to be taken sequentially. Earlier units establish foundational concepts that later units build upon. While you can explore units in any order, following the numbered sequence provides the most coherent learning experience.