The Pillars of AI Governance
AI Core Principles in Education
Master the ethical, legal, and strategic pillars of AI governance in K-12 and higher education — from policy design to responsible implementation. This program equips educators and leaders to champion trustworthy AI across their institutions.
AI Fairness in Education
Fairness in AI means ensuring that automated systems do not produce biased or discriminatory outcomes — especially for vulnerable student populations. In education, this pillar examines how AI tools must be designed, audited, and monitored to treat all learners equitably.
Topics Covered
- Understanding algorithmic bias and its causes
- Disparate impact analysis in student assessment tools
- Bias auditing frameworks for EdTech procurement
- Case studies: bias in predictive analytics and grading AI
- Designing fair AI rubrics and benchmarks for K-12
- Equity-centred AI deployment strategies
Learning Outcomes
- 1
Conduct a fairness audit of an AI tool used in your school
- 2
Identify at-risk populations affected by algorithmic decisions
- 3
Build an AI Fairness Policy for your institution
All 5 Pillars
Ready to Lead with Responsible AI?
Enrol in the AI Governance program and become the policy champion your school needs.