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EU AI ACT 2024 - Oerview

General Principles

    • Risk Categorization

      • Reference: Article 6 – Classification of AI systems.
      • High-risk systems include those impacting education per Annex III.

    • Transparency

      • Reference: Article 52 – Transparency obligations for AI systems.

    • Accountability

      • Reference: Article 23 – Governance and accountability in high-risk systems.

    • Human Oversight

      • Reference: Article 14 – Human oversight requirements for AI systems.

    • Ethical Framework

      • Reference: Article 9 – Risk management system requirements.

Data Handling

    • Data Privacy

      • Reference: Article 10 – Quality of datasets, aligned with GDPR (General Data Protection Regulation).

    • Bias Mitigation

      • Reference: Article 10 – Avoiding biases in datasets.

    • Data Security

      • Reference: Article 15 – Cybersecurity requirements for AI systems.

    • Data Transparency

      • Reference: Article 13 – Documentation requirements for high-risk systems.

    • Consent

  • Reference: Article 52 – Consent and communication obligations for users.

AI-Driven Learning Tools

    • Content Accuracy
  • Reference: Article 10 – Dataset quality assurance.
  1. Personalization
  • Reference: Article 14 – Aligning personalization with ethical oversight.
  1. Feedback Mechanism
  • Reference: Article 54 – Reporting and feedback mechanisms for AI systems.
  1. Inclusivity
  • Reference: Article 10 – Diverse datasets to ensure inclusivity.
  1. Cultural Sensitivity
  • Reference: Article 9 – Risk mitigation strategies, including cultural sensitivity.

Grading and Assessments

    • Fairness
  • Reference: Article 7 – Prohibitions of certain AI practices (unfair grading systems).
  1. Explainability
  • Reference: Article 14 – Human oversight to ensure explainability.
  1. Error Correction
  • Reference: Article 56 – Error correction and liability mechanisms.
  1. No Sole Decision-Making
  • Reference: Article 14 – Human oversight in decision-making processes.
  1. Accuracy Validation
  • Reference: Article 10 – Continuous testing for dataset and model accuracy.

Student Engagement

    • Interaction Design
  • Reference: Article 14 – Ensuring systems are designed for responsible usage.
  1. Feedback Personalization
  • Reference: Article 9 – Personalization with fairness considerations.
  1. Privacy in Chatbots
  • Reference: Article 52 – Transparency in AI communication tools.
  1. Monitoring Usage
  • Reference: Article 15 – Usage monitoring and cybersecurity protocols.
  1. Emotional AI Limitations
  • Reference: Article 5 – Prohibition of harmful or manipulative AI systems.

Training for Educators

    • AI Literacy
  • Reference: Article 9 – Training and awareness programs for stakeholders.
  1. Bias Awareness
  • Reference: Article 10 – Educator training on dataset biases.
  1. Decision Oversight
  • Reference: Article 14 – Human decision-making training requirements.
  1. Ethical Use Training
  • Reference: Article 9 – Awareness programs on ethical AI use.
  1. Policy Awareness
  • Reference: Article 23 – Internal policies for AI governance in organizations.

Procurement and Deployment

    • Supplier Compliance
  • Reference: Article 24 – Supply chain management obligations.
  1. Documentation
  • Reference: Article 13 – Comprehensive documentation of AI system operations.
  1. Risk Assessment
  • Reference: Article 9 – Risk management plan for deployment.
  1. Third-Party Audits
  • Reference: Article 20 – Conformity assessments by third parties.
  1. Regular Updates
  • Reference: Article 13 – Documentation to reflect system updates.

Special Needs and Accessibility

    • Accessibility Features
  • Reference: Article 14 – Inclusion of human oversight for accessibility.
  1. Support for Disabilities
  • Reference: Annex III – High-risk systems, including those designed for disabilities.
  1. Language Support
  • Reference: Article 10 – Dataset diversity, including multilingual data.
  1. Customizable Interfaces
  • Reference: Article 9 – Designing customizable features for inclusivity.
  1. Assistive AI Validation
  • Reference: Article 20 – Validation and testing for assistive technologies.

Long-Term Impact

    • Future-Proofing
  • Reference: Article 13 – Regular updates and adaptable documentation.
  1. Sustainability
  • Reference: Article 9 – Environmental considerations in AI usage.
  1. Cost-Benefit Analysis
  • Reference: Article 20 – Economic assessment during conformity checks.
  1. Scalability
  • Reference: Article 13 – Design requirements for scalability.
  1. Continuous Improvement
  • Reference: Article 54 – Reporting and adapting AI systems.

Stakeholder Engagement

    • Parental Involvement
  • Reference: Article 52 – Transparency obligations to inform all stakeholders.
  1. Student Participation
  • Reference: Article 54 – Mechanisms for user feedback.
  1. Community Outreach
  • Reference: Article 23 – Institutional governance including community input.
  1. Cross-Institution Collaboration
  • Reference: Article 20 – Shared practices through audits and testing.
  1. Regulatory Liaison
  • Reference: Article 62 – Coordination with regulatory authorities.
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