Course Overview

Artificial intelligence is becoming increasingly relevant across the aviation sector, supporting everything from maintenance and operations to air traffic management and unmanned systems. This course provides a comprehensive introduction to the concepts, regulatory framework, and guidance material shaping the safe and trustworthy use of Artificial Intelligence (AI) in aviation, specifically aligned with EASA’s requirements.

The curriculum comprehensively covers key AI definitions, the current aviation regulatory landscape, and the four pillars of EASA’s trustworthy AI framework: Trustworthiness Analysis, AI Assurance, Human-Centred Design, and Safety Risk Mitigation. Learners will gain a foundational understanding of how to introduce, supervise, and regulate AI applications safely, responsibly, and in accordance with emerging European expectations.

New to AI? Consider starting with our free introductory module, Artificial Intelligence for Aviation Applications.

Target Audience

“Trustworthy AI in Aviation” course has been designed for a broad aviation audience. It is highly recommended for:

• Organisations and individuals introducing AI/ML technologies to aviation use cases.
• End users like flight crews, ATCOs, or maintenance staff who need to understand AI outputs.
• Professionals involved in developing, supervising, evaluating, approving, or regulating AI technologies, including pilots, engineers, technicians, air traffic controllers, aviation psychologists, safety specialists, managers, and authority personnel.

Note: No previous experience in artificial intelligence is required. The emphasis is on understanding principles, concepts and practical implications rather than programming, mathematics or data science.

Recommended Preparation: If you want to build a foundational understanding of AI technologies before diving into the EASA regulatory framework, we highly recommend reviewing our free course: Artificial Intelligence for Aviation Applications.

Learning Outcomes

By the end of the course, learners will be able to:

Knowledge

• Explain EASA’s four-pillar AI trustworthiness framework, its core concepts (such as the W-shaped learning assurance process and Data Quality Requirements), and its relationship with the EU AI Act.
• Identify EASA’s AI classification levels (0-3) and explain the distribution of authority between humans and AI systems.
• Describe Human-AI Teaming concepts and the expanded scope of AI techniques, including reinforcement learning, symbolic AI, and hybrid AI.

Skills

• Apply EASA’s trustworthiness framework and ethics-based assessment principles to evaluate AI-enabled aviation applications.
• Classify AI applications, evaluate Human-AI Teaming risks, and propose appropriate safety risk mitigations for AI-related hazards.
• Interpret the W-shaped learning assurance process by identifying relevant Operational Design Domains (ODD) and Data Quality Requirements.
• Navigate EASA’s evolving guidance material to identify and support aviation use cases across various AI techniques.

Competency

• Contribute effectively to the evaluation, deployment, oversight, assurance, or operational use of AI-enabled aviation systems within the context of EASA’s evolving trustworthiness framework.

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