2024/09/13 by Hymalai Bello, Daniel Geißler, Bello, Hymalai +15
Decision Sciences · Health Professions · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Occupational Health and Safety Research #Quality and Safety in Healthcare #Risk and Safety Analysis
paper · pdf · doi:10.48550/arxiv.2409.08666
openalex publication_date 2024/09/13 · openalex created_date 2024/10/23 · openalex updated_date 2026/07/28
Artificial Intelligence (AI) methods are powerful tools for various domains, including critical fields such as avionics, where certification is required to achieve and maintain an acceptable level of safety. General solutions for safety-critical systems must address three main questions: Is it suitable? What drives the system's decisions? Is it robust to errors/attacks? This is more complex in AI than in traditional methods. In this context, this paper presents a comprehensive mind map of formal AI certification in avionics. It highlights the challenges of certifying AI development with an example to emphasize the need for qualification beyond performance metrics.