Foundations of AI and Law

Course Objectives

The objectives of this course are to;

1. Introduce, describe, and contextualize the core AI technologies—Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Large Language Models, and Generative AI.
2. Explore global perspectives on AI adoption within legal systems of the United States, United Kingdom, European Union, and Africa, drawing implications for Uganda.
3. Contrast AI model reasoning (predictive, probabilistic, black-box) with doctrinal legal reasoning (rule-based, analogical, interpretive).
4. Examine the regulatory and ethical landscape of AI and its implications for lawyers, judges, and legal policymakers.
5. Apply AI platforms in legal research, discovery, and drafting while recognizing and mitigating risks of hallucination, fabricated references, and over-reliance.
6. Develop practical competence in conducting e-discovery, automated review of large document sets, and AI-assisted drafting for litigation and advisory work.

Learning Outcomes

By the end of this course, a learner will be able to;

1. Define and explain key AI concepts, their functioning, and relevance to legal practice.
2. Compare and contrast AI reasoning with legal doctrinal reasoning in precedent-based systems.
3. Evaluate the potential, limitations, and risks of generative AI in legal work, including hallucinations and bias.
4. Conduct accurate and efficient legal research using AI-powered platforms while verifying results against authoritative sources.
5. Apply e-discovery tools to litigation workflows, ensuring efficiency, integrity, and compliance.
6. Map global regulatory frameworks (EU AI Act, GDPR, ABA guidelines, CCBE, IBA, AU strategies) against Uganda’s evolving legal framework.
7. Articulate the implications of AI adoption for legal education, practice, and policy in Uganda.

Outline of Content

1. History and Evolution of AI in Law

• • Early expert systems and rule-based reasoning.
  • Emergence of LegalTech (e-discovery, databases, automation).
  • Predictive analytics, generative AI, and their entry into legal systems.
  • Core AI Technologies for Lawyers
  • Machine Learning and Deep Learning: classification, prediction, risk scoring.
  • Computer Vision: applications in forensic and evidentiary practice.
  • Natural Language Processing: legal search, summarization, chatbot Q&A.
  • Large Language Models (GPT-4/5, Harvey AI, Law Notion).
  • Generative AI: producing legal drafts, images, synthetic data.

2. Generative AI Capabilities for Law

• • Drafting contracts, pleadings, and legal opinions.
  • Presentation building, argument generation.
  • Creation of visual/audio evidence; authenticity and deepfake challenges.

3. AI vs Human Legal Reasoning

• • Rule-based logic vs analogical precedent-based reasoning.
  • Black-box models vs transparent judicial reasoning.
  • Debates on whether AI can simulate “legal judgment.”
  • AI in Legal Research and e-Discovery
  • Traditional vs AI-augmented research.
  • Case studies on AI errors (fabricated citations).
  • Leading AI research platforms (Westlaw AI, Lexis+ AI, Casetext, Harvey AI).
  • AI in litigation: predictive coding, relevance ranking, privilege detection.
  • Practical workflows for discovery, disclosure, and compliance.

4. Regulatory and Ethical Frameworks

• • EU AI Act and GDPR.
  • ABA and US case law on AI competence.
  • UK judicial and administrative adoption.
  • African Union AI Strategy and implications for Uganda Law Society.
  • Role of IBA, CCBE, and international professional bodies.

5. Practical Lab: Research Integrity and E-Discovery

• • Use AI platforms to draft a legal memo.
  • Cross-check citations in authoritative databases.
  • Run predictive coding exercise on a sample dataset.
  • Reflection on balancing efficiency with diligence.

Reference List

1. Introduction to AI and Law: https://www.scribd.com/document/554650871/Course-Introduction-AI-and-Law

2. Waisberg and A. Hudek (2021). AI for Lawyers. How Artificial Intelligence is adding value, amplifying expertise, and transforming careers. John Wiley & Sons, Inc. ISBN 9781119723899 (ePDF).
3. Schiffner. Artificial Intelligence in Legal Practice. Benefits, Considerations, and Best Practices. https://www.dri.org/docs/default-source/dri-white-papers-and-reports/ai-legal-practice.pd
4. Pietropaoli. Use of Artificial Intelligence in Legal Practice. British Institute of International and Comparative Law.
   https://www.biicl.org/documents/170_use_of_artificial_intelligence_in_legal_practice_final.pdf

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