Accountable and Trustworthy AI Practices

This unit examines how organizations balance innovation with accountability by exploring laws, liability, corporate responsibility, and leading practices for responsible AI. Students learn to operationalize trust through people, processes, and technologies and produce actionable guidelines and plans to implement trustworthy AI.

Learning Objectives

• Analyze legal, regulatory, and liability issues related to AI deployments by mapping case studies to applicable statutes, precedents, and risk scenarios
• Evaluate leading practices for accountable and responsible AI (including governance, transparency, explainability, and risk mitigation) using a rubric to assess organizational readiness
• Apply a people-process-technology framework to design an implementation plan that cultivates trust in AI systems, specifying roles, controls, and technical safeguards
• Develop an actionable organizational guideline for trustworthy AI that balances innovation and accountability and includes monitoring, remediation, and stakeholder communication steps