01
Why AI Ethics Matters Now
The business, legal, and human case for responsible AI. Real-world harms and why organizations can no longer afford to ignore AI ethics.
Foundations
06
AI Governance Frameworks
NIST AI RMF, EU AI Act, UNESCO Recommendation. How to choose and implement the right framework for your organization.
Frameworks
02
Core AI Ethics Principles
The seven foundational principles: Fairness, Transparency, Accountability, Privacy, Safety, Inclusivity, and Human Oversight.
Principles
07
Building Your AI Ethics Committee
Who should be at the table, what the committee does, how to structure meetings, and how to handle AI incidents and escalations.
Governance
03
AI Bias — Understanding & Mitigation
Types of bias, how they enter AI systems, real-world case studies, and practical bias testing and mitigation strategies.
Bias & Fairness
08
Sector-Specific AI Ethics
Tailored guidance for nonprofits, higher education, small business, and healthcare. Sector-specific risks, regulations, and best practices.
Applied Ethics
04
AI Transparency & Explainability
What explainable AI means, why it matters for trust and accountability, and how to communicate AI decisions to stakeholders.
Transparency
09
AI Policy Development
Step-by-step guide to writing your AI Use Policy, Employee AI Guidelines, and Vendor AI Requirements. Templates included.
Policy
05
Data Privacy & AI
GDPR, CCPA, and AI data governance. How AI systems collect, use, and risk personal data — and how to protect your organization.
Privacy & Data
10
Your AI Governance Roadmap
The AI Governance Maturity Model, your 90-day action plan, and how to sustain ethical AI leadership over time.
Action Planning