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

20 minutes per unit

Curriculum Map

What You Will Learn

Competence & Supervision

Model Rule 1.1 requires competence with AI tools. Learn the verification duties, supervision obligations, and hallucination risks.

Confidentiality

When client data enters an AI system, privilege and confidentiality obligations follow. Vendor due diligence and consent requirements.

AI in Litigation

Predictive coding validation, TAR protocols, opposing counsel objections, and Daubert challenges to AI-generated evidence.

All Units

20 minutes

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.

•Identify the primary applications of AI in legal practice including legal research, document review, and contract analysis
•Distinguish between proven AI capabilities and overstated vendor claims in legal technology
•Assess the technical limitations of current AI systems that affect legal accuracy and reliability

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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.

•Apply ABA Model Rule 1.1 competence requirements to the use of AI in legal service delivery
•Establish supervisory protocols for non-lawyer staff and junior attorneys using AI tools
•Identify the verification steps required when AI output informs legal advice or court submissions

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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.

•Identify the confidentiality risks under Model Rule 1.6 when client data is processed by AI vendors
•Assess whether attorney-client privilege is waived when confidential communications are input into AI systems
•Establish protocols for client consent and vendor due diligence when using cloud-based AI tools

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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.

•Explain the legal standards for using technology-assisted review (TAR) and predictive coding in e-discovery
•Identify the validation and transparency requirements courts impose on parties using AI for document review
•Assess when AI-generated evidence or expert testimony may face Daubert challenges regarding reliability

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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.

•Identify the sources of algorithmic bias in AI systems including training data bias and proxy discrimination
•Assess the legal risks under civil rights laws when AI tools produce disparate impact outcomes
•Evaluate the ethical obligations of attorneys who recommend or challenge AI systems with known bias issues

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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.

•Assess how AI automation of routine legal tasks will affect law firm economics and billing models
•Identify the evolving competency requirements for attorneys as AI handles tasks previously performed by junior lawyers
•Evaluate AI's potential to expand access to justice by reducing the cost of legal services

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