1. Algorithms and data
1.1 Explainability of algorithms
One of the major obstacles to the use of AI lies in the explicability of algorithms, particularly those of complex models such as deep neural networks. These algorithms often operate like "black boxes", making it difficult for users to understand the decisions made by the AI. This opacity poses ethical and practical problems, particularly in sensitive fields such as health or justice, where decisions need to be justified, and engineering, where the results of calculations need to be mastered
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Bibliography
Directory
Organizations – Federations – Associations (non-exhaustive list)
AI for Humanity
https://www.inria.fr/sites/default/files/2021-06/PNRIA-Flyer_National_EN.pdf
Association Aristote
Symposiums and conferences
Distributed Event-based Systems
https://dl.acm.org/conference/debs
International Conference on Big Data
https://ieeexplore.ieee.org/xpl/conhome/1802964/all-proceedings
...
Scientific journals
Applied Intelligence
https://link.springer.com/journal/10489
Artificial Intelligence
https://www.sciencedirect.com/journal/artificial-intelligence
Artificial Intelligence...
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