Trustworthy AI in Education

What is the aim of the AI Act proposed by the Commission regarding high-risk AI systems?

Which key requirement focuses on ensuring that AI systems respect individual rights and are subject to oversight?

Which requirement encourages stakeholder participation and addresses diversity in the use of AI systems?

Why is transparency considered a crucial requirement for AI systems in education?

What concern does the requirement for societal and environmental wellbeing particularly address?

Which of the following is NOT a part of the ethical requirements for trustworthy AI systems in education?

What aspect does accountability in AI systems require?

Which requirement emphasizes the integrity and quality of data in AI systems?

Trustworthy AI in Education

The European Commission's AI Act proposes legally binding requirements for high-risk AI systems.
These requirements focus on mitigating risks of bias and errors, especially in education and vocational training.
The AI Act aims to ensure trustworthiness of high-risk AI systems through certifications provided by developers.
Even for AI systems not falling under the AI Act, ethical requirements for trustworthy AI are encouraged for developers.
Educational institutions are advised to be aware of these requirements and consider their implications for AI usage.
The AI HLEG Ethics Guidelines for Trustworthy AI provide a framework for assessing AI systems in education.

Key Trustworthy AI Requirements

Human Agency and Oversight: Prioritizes human autonomy, oversight, and protection of fundamental rights, especially for children.
Transparency: Emphasizes traceability, explainability, and clear communication regarding AI system functionalities.
Diversity, Non-Discrimination, and Fairness: Promotes inclusive access, universal design, unbiased decision-making, and stakeholder participation.
Societal and Environmental Wellbeing: Considers sustainability, environmental impact, social consequences, and democratic values.
Privacy and Data Governance: Respects data privacy, ensures data quality and integrity, and provides access to relevant data.
Technical Robustness and Safety: Focuses on resilience to attacks, security, accuracy, reliability, and reproducibility of AI systems.
Accountability: Includes auditability, mitigation of negative impacts, transparency around trade-offs, and mechanisms for redress.

Explore the European Commission's AI Act and its implications for high-risk AI systems in education. This quiz covers the key requirements for trustworthy AI, including human oversight and transparency, as well as ethical considerations for educational institutions. Test your knowledge on how these regulations shape the future of AI in learning environments.