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AI and Law

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AI and Law

Last Updated : August 1, 2025
F4courses
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About Course

This interdisciplinary course thoroughly examines the
rapidly evolving intersection of artificial intelligence and
legal systems. It explores how AI technologies—including
document automation, predictive analytics, and
regulatory compliance—are fundamentally reshaping
traditional legal practice. Concurrently, the course
delves into the complex legal and ethical frameworks
governing AI development and deployment, such as
data privacy, intellectual property, and algorithmic bias.
Students will gain practical skills in designing and
implementing AI solutions for legal applications,
alongside a comprehensive understanding of the
intricate regulatory landscape and ethical
responsibilities in this crucial domain.

What Will You Learn?

  • Critically assess current AI applications in legal research, e-discovery, contract management, and litigation support
  • Apply advanced machine learning and natural language processing (NLP) techniques to analyze legal documents, predict case outcomes, and automate legal workflows
  • Design and develop AI systems that comply with established legal regulations, ethical guidelines, and professional responsibility standards, including GDPR and CCPA.
  • Analyze and interpret evolving legal and regulatory frameworks for AI technologies, encompassing liability, accountability, and explainability mandates across jurisdictions.
  • Evaluate complex liability considerations, intellectual property rights (e.g., copyright for AI-generated content, patentability of AI inventions), and data
  • ownership issues pertinent to AI systems.
  • Formulate and implement approaches to ensure fairness, transparency, and explainability in AI-driven legal decision-making processes, addressing potential biases and promoting equitable outcomes.

Course Content

AI Applications in Legal Practice
Explore specific AI tools and platforms for enhanced legal research (e.g., Ross Intelligence, LexisNexis AI), automated document review (e.g., Kira Systems, Relativity AI), sophisticated contract analysis (e.g., legal AI platforms for clause identification), predictive case outcome modeling, and optimized e- discovery processes. Cover AI in legal workflow automation, expert systems for initial legal advice, and due diligence automation in M&A

Legal Text Analytics & NLP
Focus on advanced NLP techniques for unstructured legal documents, including legal information extraction and summarization (e.g., key facts, dates, parties), citation analysis and precedent mapping, automated contract provision classification, and sophisticated risk assessment from legal texts. Develop NLP-driven statutory interpretation and legal question-answering systems leveraging large language models (LLMs)

Predictive Legal Analytics
Examine the development and application of machine learning models for predicting various legal outcomes. Topics include case outcome prediction (e.g., patent litigation, criminal sentencing), judicial decision analysis using historical data, estimating settlement values, and comprehensive litigation risk assessment. Discuss methodologies for strategic case planning informed by predictive analytics and rigorous model evaluation in specific legal contexts

AI Regulation & Governance
Address the global landscape of AI regulatory frameworks (e.g., EU AI Act, US National AI Initiative, China's AI regulations), specific compliance requirements, and their intersection with existing data protection and privacy laws (e.g., GDPR, CCPA). Cover emerging AI-specific legislation, voluntary standards, and evolving liability regimes for autonomous AI systems. Explore AI certification and auditing approaches, and prognosticate on the future trajectory of AI regulation and international harmonization efforts

Intellectual Property & AI
Explore the complex IP landscape surrounding AI: patentability of AI-generated inventions, copyright for works created by AI algorithms, trade secret protection for proprietary AI models and training data, and IP licensing models for AI technologies. Discuss open-source AI considerations, data rights, ownership issues pertaining to AI outputs, and strategies for global IP protection in the AI era.

Ethics & Justice in Legal AI
Cover critical ethical dimensions, including fairness and bias detection/mitigation in legal algorithms (e.g., sentencing, bail decisions), ensuring due process in automated decision-making, and improving access to justice through AI-powered legal aid. Address practical implementation of transparency and explainability requirements (XAI) in legal contexts, professional responsibility for legal practitioners using AI, and models for effective human oversight and intervention in AI-driven legal processes.

Capstone Project
Students will conceptualize, design, and develop a working AI solution for a specified legal application, such as an automated contract review tool for identifying specific clauses related to force majeure, a specialized legal research assistant for environmental law cases, a predictive model for civil lawsuit outcomes in a specific jurisdiction, or a real- time compliance monitoring system for data privacy regulations (e.g., GDPR adherence). Alternatively, students may conduct a comprehensive legal and ethical analysis of an emerging AI technology or a specific regulatory framework governing AI in a defined domain or jurisdiction (e.g., AI in criminal justice). All projects must rigorously consider legal accuracy, ethical implementation protocols, data security, and professional responsibility.

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