Recent progress in Artificial Intelligence, especially in Machine Learning, has aroused unprecedented interest in these technologies. Many industrial sectors are now considering using them. However, this has led to strong scientific obstacles. Machine learning, especially deep neural networks, can perform well enough to consider critical applications such as autonomous vehicles, predictive maintenance and medical diagnosis, but their theoretical properties are not well-known yet. These scientific challenges make it difficult to meet the industrial constraints required for a general application such as certification, qualification and explainability of algorithms. It is from these observations that the DEEL Project emerged in September 2017.

Research teams in Quebec and France are currently working on the development of this dependable, robust and explainable artificial intelligence within the context of the DEEL (DEpendable and Explainable Learning) project. 

The DEEL project is overseen by the Institute for Data Valorization (IVADO), the IRT Saint Exupéry, the Consortium for Research and Innovation in Aerospace in Quebec (CRIAQ), Artificial and Natural Intelligence Toulouse Institute (ANITI) and IID, Institute Intelligence and Data at Université Laval, in collaboration with numerous members.