In this interdisciplinary project, we were developing models based on the interaction between human and artificial intelligence to facilitate learning.
The goal was to develop an AI system which combines a model-based approach and machine learning that can be used for causal analysis of errors and accidents in complex areas, be it traffic accidents or misdiagnoses. To achieve this, the AI system will continue to learn by interacting with technical experts so as to build increasingly accurate causal models.
This combination of explainable and interactive learning is an innovative approach designed to make machine learning applicable for supporting experts within complex and safety-critical socio-technical areas.
The project was terminated.