This unit examines governance, ethics, trust, and organizational strategies required for responsibly adopting AI in nonprofit settings. Students learn to evaluate AI solutions against trust and fairness criteria, design multidisciplinary implementation plans that include change management and human oversight, and identify legal, privacy, technical, and cultural risks with mitigation strategies.
Learning Objectives
- Analyze case studies and organizational scenarios to identify ethical, cultural, and technical challenges that affect nonprofit AI adoption
- Evaluate AI tools and vendors using defined criteria (trust, bias, privacy, security, legal compliance, and potential harms) and identify red flags
- Design a multidisciplinary implementation plan that incorporates change management, human oversight, iterative R&D, and mechanisms to preserve stakeholder trust
- Assess regulatory, privacy, bias, and operational risks associated with proposed AI solutions and propose concrete mitigation strategies aligned with nonprofit values
Curriculum
- 1 Section
- 39 Lessons
- 30 hours
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- Unit 3 — Ethical AI Governance and Implementation39
- 1.1Case Study: Education Resource Strategies20 mins
- 1.2Conclusion20 mins
- 1.3The Importance of Change Management in AI Adoption20 mins
- 1.4Strategies for Successful AI Implementation20 mins
- 1.5Setting Up a Multidisciplinary Team for Success20 mins
- 1.6Why a Multidisciplinary Team Is Essential20 mins
- 1.7Failing Fast: AI Is Iterative by Design20 mins
- 1.8Investing in Philanthropic R&D20 mins
- 1.9The Need for Perpetual Adaptation: Lessons from History20 mins
- 1.10AI Is Here to Stay—Adapt or Get Left Behind20 mins
- 1.11Upholding Ethical Standards: AI Aligned with Values20 mins
- 1.12Currency of Trust: The Nonprofit Sector’s Most Valuable Asset20 mins
- 1.13Ethical According to Whom?: Measuring AI Perceptions from an End User’s Perspective20 mins
- 1.14The Unique Role of the Nonprofit Sector in AI Governance20 mins
- 1.15AI Advances Exponentially: Keeping Your AI Framework Adaptable20 mins
- 1.16The Responsible and Beneficial AI Framework20 mins
- 1.17Human Oversight: Keeping Humans in Control of AI Decisions20 mins
- 1.18Ethical versus Legal Considerations: Navigating the Gray Areas20 mins
- 1.19Data Privacy and Security: Protecting Sensitive Information20 mins
- 1.20Bias and Fairness: Ensuring AI Systems Are Fair and Unbiased20 mins
- 1.21The Role of Legislation: Navigating the Regulatory Landscape20 mins
- 1.22A Higher Standard to Promote and Protect Trust20 mins
- 1.23Criteria for Evaluation: Key Factors for AI Selection20 mins
- 1.24Does the AI Prioritize, Protect, and Promote Trust?20 mins
- 1.25Red Flags: Warning Signs of Potentially Harmful AI Solutions20 mins
- 1.26The Ever‐Evolving Nature of AI: Why Evaluations Must Be Reassessed Frequently20 mins
- 1.27Humanity over Utility: A Moral Imperative20 mins
- 1.28Trading Privacy for Convenience: A Faustian Bargain?20 mins
- 1.29Provocative Questions for the Nonprofit Sector20 mins
- 1.30Humanity as the Guiding Principle20 mins
- 1.31The Need for Deliberation: Prioritizing Humanity in AI20 mins
- 1.32Case Study: The Dangers of Over‐optimizing for Utility20 mins
- 1.33Analogies in the Nonprofit World: The Hammer and the Hand20 mins
- 1.34Human Oversight: The Need for Continuous Human Control20 mins
- 1.35Humanity over Utility—A Moral Imperative20 mins
- 1.36Cultural Challenges: No Vision versus Too Much Vision20 mins
- 1.37Jumping into the Deep End20 mins
- 1.38Cultural Resistance20 mins
- 1.39Technical Challenges20 mins
Instructor
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