Responsible AI: Ethics and Governance

This unit examines the ethical, legal, social, and security implications of AI systems, including bias amplification, accountability, data protection, and regulation. Students will learn governance strategies, team roles, and communication practices to set realistic expectations and prepare AI projects for safe, equitable deployment.

Learning Objectives

• Analyze case studies to identify sources of bias, safety vulnerabilities, privacy risks, and socio-economic impacts in AI systems and cite at least three contributing factors for each case
• Evaluate governance frameworks, regulatory approaches, and organizational policies to recommend appropriate mitigation, accountability, and transparency measures for specified AI scenarios
• Apply data protection and security best practices to design a privacy-preserving data handling and access control plan for an AI project that addresses consent, anonymization, and incident response
• Demonstrate professional team roles and communication strategies by creating a three-way conversation and expectation-setting plan (developer, stakeholder, impacted community) for deployment, monitoring, and remediation