AI Policy and Governance

The Ethical Mirror: What governance structures ensure a fair and accurate reflection?

Essential Question

What governance structures and policy frameworks can ensure that AI in education serves as an ethical mirror that fairly and accurately reflects our educational values and goals?

Learning Objectives

  • Analyze existing policy frameworks for educational AI from global, national, and institutional perspectives
  • Evaluate different approaches to AI governance in educational contexts
  • Design policy recommendations for ethical AI implementation
  • Develop implementation strategies for AI governance at different levels

Today's Agenda

  1. Opening activity: The Policy Dilemma
  2. Interactive lecture: AI policy frameworks and governance approaches
  3. Break
  4. Applied learning: Policy Development Workshop
  5. Policy Priority Ranking
  6. Closing thoughts and preview

Opening Activity: The Policy Dilemma

Scenario: Mountain View University is implementing an AI-powered advising system that will analyze student data (including grades, course selections, extracurricular activities, and campus movement patterns) to provide personalized academic recommendations. The university must develop a governance policy for this system.

Consider your assigned stakeholder role:

  • What values and concerns does your stakeholder bring to this policy discussion?
  • What safeguards or requirements would your stakeholder consider essential?
  • Where might there be tensions between different stakeholder interests?
  • How might these tensions be resolved in a balanced policy framework?

Part 1: Policy Landscapes

Global Frameworks

UNESCO AI Ethics Recommendation:

  • Protection and promotion of human rights
  • Environment and ecosystem flourishing
  • Ensuring diversity and inclusiveness
  • Living in peaceful, just, and interconnected societies

OECD AI Principles:

  • Inclusive growth, sustainable development, and well-being
  • Human-centered values and fairness
  • Transparency and explainability
  • Robustness, security, and safety
  • Accountability

National Approaches

Executive Order on Advancing AI Education for American Youth:

  • Presidential AI Challenge
  • Improving education through AI
  • Enhancing training for educators
  • Promoting registered apprenticeships
  • Integration of AI skills across curriculum

National AI Strategies in Education:

  • Varied approaches to balancing innovation and regulation
  • Different cultural and governance contexts
  • Emerging consensus on ethical principles
  • Divergent implementation mechanisms

Institutional Frameworks

EDUCAUSE Action Plan Framework:

  • Governance
  • Data governance, evaluation, monitoring usage
  • Inclusive access, intellectual property
  • Operations
  • Professional development, infrastructure
  • Implementation recommendations
  • Pedagogy
  • Academic integrity, assessment
  • Student competencies, algorithmic bias

SAFE-T Framework:

  • Stakeholder-Aligned Fairness, Ethics, Transparency
  • Trust formation through transparency mechanisms
  • Algorithmic fairness and bias mitigation strategies
  • Accountability in AI decision-making
  • Data privacy and security mechanisms

Think-Pair-Share Activity

Think: Which policy principles do you find most essential for educational contexts?

Pair: Discuss with a partner:

  • Why did you select these principles?
  • How might they be implemented in practice?
  • What tensions might arise between different principles?

Share: Key insights from conversations

Part 2: Governance Approaches

Self-Regulation Models

Institutional Policies:

  • Developed internally by educational institutions
  • Adapted to specific contexts and needs
  • May lack standardization and enforcement mechanisms
  • Often more flexible and adaptable to changing technologies

Professional Standards:

  • Developed by educational/professional associations
  • Create field-wide norms and expectations
  • Implementation varies across institutions
  • Peer accountability mechanisms

Co-Regulation Models

Public-Private Partnerships:

  • Collaboration between government and industry
  • Flexible frameworks with regulatory backstops
  • Balancing innovation with protection
  • Examples: Age-appropriate design codes, education data cooperatives

Multi-Stakeholder Governance:

  • Diverse representation in decision-making
  • Distributed accountability mechanisms
  • Ongoing dialogue and adaptation
  • Challenges in representation and power dynamics

Legislative Frameworks

Data Protection Laws:

  • GDPR, FERPA, COPPA, state privacy laws
  • Rights-based approaches to data governance
  • Compliance requirements and enforcement
  • Cross-border data flows and jurisdictional challenges

AI-Specific Regulations:

  • Emerging frameworks for high-risk AI systems
  • Sector-specific requirements for education
  • Compliance verification and auditing
  • International alignment challenges

Comparative Analysis

In small groups, analyze your assigned governance approach:

  • What are the key strengths and limitations?
  • What stakeholders are empowered or potentially marginalized?
  • How adaptable is this approach to rapidly evolving AI technologies?
  • What implementation challenges might arise in educational contexts?

Part 3: Implementation Challenges

Technical Complexity

Knowledge Gaps:

  • Understanding AI systems and capabilities
  • Translating technical concepts into policy language
  • Evaluating AI system compliance
  • Maintaining currency with technological change

Assessment Challenges:

  • Measuring algorithmic bias
  • Evaluating transparency and explainability
  • Assessing educational effectiveness
  • Developing meaningful audit mechanisms

Resource Disparities

Across Institutions:

  • Varied technical expertise and capacity
  • Different levels of funding and infrastructure
  • Rural/urban and socioeconomic divides
  • Implementation support needs

Within Institutions:

  • Departmental differences in AI readiness
  • Faculty/staff training and support
  • Student digital literacy variations
  • Governance capacity limitations

Balancing Innovation and Protection

Innovation Enablers:

  • Creating safe spaces for experimentation
  • Appropriate risk levels for different contexts
  • Adaptive governance and policy evolution
  • Learning from implementation experiences

Protection Mechanisms:

  • Safeguards for vulnerable populations
  • Risk assessment frameworks
  • Redress and appeal processes
  • Ongoing monitoring and evaluation

Scenario Exploration

For your assigned implementation challenge:

  • How might different stakeholders perceive this challenge?
  • What potential solutions could address this challenge?
  • What trade-offs might be involved in different approaches?
  • How could policy frameworks adapt to address this challenge?

Part 4: Stakeholder Engagement

Student Participation

Engagement Mechanisms:

  • Student representation in governance bodies
  • Feedback channels and advisory roles
  • Student-led initiatives and advocacy
  • Education and capacity building

Ensuring Diverse Student Voices:

  • Representation across programs and levels
  • Inclusion of marginalized student perspectives
  • Addressing power imbalances
  • Supporting meaningful participation

Faculty and Administrator Perspectives

Faculty Governance:

  • Academic freedom considerations
  • Pedagogical autonomy and AI implementation
  • Research ethics and AI applications
  • Professional development needs

Administrative Leadership:

  • Strategic alignment with institutional mission
  • Resource allocation and prioritization
  • Risk management and legal compliance
  • Change management approaches

Cross-Institutional Collaboration

Knowledge Sharing Networks:

  • Communities of practice
  • Consortia and associations
  • Policy repositories and templates
  • Case studies and implementation examples

Collaborative Governance Models:

  • Shared policy development
  • Joint implementation initiatives
  • Resource pooling and collective action
  • Amplifying advocacy for policy change

Industry and Community Engagement

Vendor Accountability:

  • Procurement requirements and standards
  • Transparency expectations
  • Alignment with educational values
  • Ongoing assessment and feedback

Community Participation:

  • Parent/guardian engagement in K-12 contexts
  • Employer and workforce perspectives
  • Civil society organization partnerships
  • Public communication and education

Gallery Walk Activity

Review the stakeholder engagement strategies posted around the room:

  • Add comments on potential challenges or opportunities
  • Identify best practices for your educational context
  • Note connections to policy frameworks we've discussed
  • Be prepared to share insights with the class

Applied Learning: Policy Development Workshop

Exit Ticket