This is to announce the International Workshop on Designing the Conceptual Landscape for a XAIR Validation Infrastructure (DCLXVI 2024).It is organized by the EMMC-related project BatCAT (HEur GA no. 101137725) in collaboration with the project AI4Work (HEur GA no. 101135990) and will be held on 11th December 2024 at RPTU Kaiserslautern. At the workshop, we will be discussing the core concepts for explainable-AI-ready models and data. These concepts include, but are not limited to:
- Explainability and explanation
- Reproducibility, reliability, and reliance
- Opacity and transparency, interpretability and interpretation
- DIKW: Data, information, knowledge, and wisdom
- Responsibility, trust, trustworthiness and reasons/motivations for trusting
- Model design, parameterization, and optimization
- Holistic validation and unit testing (of models and simulation codes)
- Theoretical virtues (of models)
- Epistemic agents, vices, and virtues
- The four elements of “FAIR,” possibly requiring a revision or update
- Simulation; applying and evaluating models
- Context awareness, subject matter, and logical subtraction
In particular, we will discuss how we need to go beyond the FAIR principles of research data management to make models and data explainable-AI-ready (XAIR), so that they become “FAIR and XAIR.”Submission deadline: 19th October 2024. The proceedings will be published in the Springer LNNS series (Lecture Notes in Networks and Systems).Read more on organisation, submission and programme …
