Topics

The goal of this symposium is to grow a community of researchers and practitioners for AI trustworthiness assessment leveraged by AI science, system and software engineering, metrology, and SSH. It aims to explore innovative approaches, metrics, methods and tools, with a particular focus on the following topics (but not limited to):

• Dataset qualification
• Performance indicators (accuracy, robustness, etc.)
• Test examples generation
• Risks and vulnerabilities
• Non-functional requirements such as accountability, reliability, privacy etc.
• Explainability and interpretability
• Trustworthiness measure and trade-offs (metrics, indicators…)
• Processes and governance mechanisms in organizations
• Sectorial specificities, applications