Trust, Accountability, and Responsible AI

This unit equips learners to balance innovation with accountability by examining legal liability, corporate responsibility, and leading practices for trustworthy AI in law and public service contexts. Students will apply a practical trust-assessment framework, design governance measures, and prepare stakeholder-facing guidance to implement responsible AI actions.

Learning Objectives

• Analyze relevant laws, lawsuits, and liability scenarios that affect AI deployment in law, public safety, corrections, and security, citing applicable legal principles and potential organizational exposures.
• Develop a corporate or organizational accountability plan for an AI system that integrates leading practices, compliance controls, oversight mechanisms, and remediation procedures.
• Apply a stepwise trust-assessment framework to a real or simulated AI use case by identifying dimensions of trust and recommending people, process, and technology interventions prioritized by impact and feasibility.
• Demonstrate the ability to communicate guidelines and recommended next steps to diverse stakeholders through a briefing or policy memo that explains trade-offs (good/better/best), legal/ethical considerations, and implementation milestones.