Responsible AI Strategy for Nonprofits

This unit examines real-world AI case studies and translates lessons into practical, ethical, and scalable AI strategies for nonprofit organizations. Students learn to identify benefits and risks, detect and mitigate bias, establish governance and privacy safeguards, and create actionable adoption and staffing plans for generative and applied AI.

Learning Objectives

• Analyze at least two AI case studies to identify a minimum of three potential benefits and three potential risks for nonprofit programs and operations
• Evaluate sources and types of bias in AI systems using two detection techniques and recommend at least three mitigation strategies tailored to a nonprofit context
• Develop a responsible AI governance and privacy/security plan that includes at least five policy elements (e.g., data handling, consent, oversight, accountability, and vendor management) for deployment or partnership scenarios
• Design a 12-month generative AI adoption roadmap that includes timeline milestones, a staffing and volunteer training plan, a basic budget estimate, partnership opportunities, and two metrics for measuring scalable, sustainable impact