AI Governance, Ethics, and Regulation

Course Objectives

The objectives of this course are to;

1. Identify ethical and legal risks associated with AI in legal practice.
2. Apply regulatory frameworks, including EU AI Act, GDPR, and Uganda Data Protection Act, to AI adoption.
3. Develop firm-level AI policies and implement vendor due diligence for AI tools.
4. Ensure professional responsibility and client confidentiality are upheld in AI-assisted workflows.

Learning Outcomes

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

1. Explain ethical, legal, and professional risks of AI in legal practice.
2. Implement responsible AI usage policies at the firm level.
3. Evaluate AI vendors using structured criteria for security, compliance, and bias mitigation.
4. Apply regulatory requirements (EU AI Act, GDPR, Uganda Data Protection Act) in AI adoption decisions.
5. Conduct risk assessments and implement governance frameworks for AI-assisted legal operations.

Outline of Content

1. Accuracy, Liability, and Professional Responsibility
   • Understanding AI limitations: error rates, false positives/negatives, and predictive uncertainty.
   • Professional accountability when using AI outputs in legal advice or litigation strategy.
   • Case studies: liability arising from AI-assisted decisions in law.
   • Guidelines for validating AI-generated outputs before client use.
2. Confidentiality, Privilege, and Client Data Protection
   • Maintaining attorney-client privilege in AI-assisted communications.
   • Risks of data leaks, re-identification, and third-party AI processing.
   • Best practices for secure AI integration: encryption, anonymization, and access control.
3. AI Ethics Frameworks and Regulatory Compliance
   • EU AI Act: Risk-based categorization of AI applications, mandatory documentation, and transparency.
   • GDPR: Data protection principles, automated decision-making rules, and client consent.
   • Uganda Data Protection Act: Local data protection requirements for personal data processing.
   • Professional ethical guidance: CCBE, ABA, and other legal ethics standards relating to AI.
   • Practical examples of compliance checks and audits.
4. Vendor Due Diligence and Procurement
   • Evaluating AI vendors for accuracy, bias mitigation, security, and compliance.
   • Contractual clauses to include: liability, data handling, audit rights, and termination conditions.
   • Risk assessment framework for selecting AI tools for legal practice.
5. Lab / Practical Exercise

• • Task: Draft a comprehensive AI usage policy for a law firm.
  • Components to include:
    • Purpose and scope of AI deployment.
    • Roles and responsibilities of users.
    • Data privacy and client confidentiality safeguards.
    • Procedures for auditing AI outputs and handling errors.
    • Vendor management and review protocols.
  • Peer review and discussion of drafted policies to ensure practical applicability.

Reference List

1. Ashley, K. D. (2017). Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age. Cambridge University Press. DOI: https://doi.org/10.1017/9781316761380
2. Susskind, R. (2019). Tomorrow’s Lawyers: An Introduction to Your Future (3rd Ed.). Oxford University Press. ISBN: 9780192864727 Book summary: https://youtu.be/I3nSSZPYIw0
3. The Cambridge Handbook of Artificial Intelligence: Global Perspectives on Law and Ethics (2022). Cambridge University Press. DOI: https://doi.org/10.1017/9781009072168

Professional Reports and White Papers

1. BIICL (2023). Use of Artificial Intelligence in Legal Practice. Excellent overview of AI tools in research, contracts, litigation, and ethics.
2. CCBE (2022). AI4Lawyers: A Practical Guide. European perspective on AI adoption in legal practice.
3. IBA (2021). The Future is Now: AI and the Legal Profession. International Bar Association’s forward-looking report.
4. DRI (2023). AI in Legal Practice (White Paper). Practical applications of AI for litigation, client service, and compliance.
5. ABA (American Bar Association) Reports. Especially on “Technological Competence” and ethical obligations when using AI.
6. NACM (2023). AI and the Practice of Law: White Paper. Focused on courts and case management applications.

Policy and Regulatory Frameworks

1. European Union Artificial Intelligence Act (2021–2025 drafts). Key regulation on AI risk categories and legal compliance.
2. African Union (2022). Continental AI Strategy. Useful for contextualizing AI in African jurisdictions.
3. Uganda’s Data Protection and Privacy Act (2019). Critical for confidentiality and evidence issues.
4. General Data Protection Regulation (GDPR, EU 2018). The gold standard for privacy compliance, relevant to cross-border practice.

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