| Issue |
ITM Web Conf.
Volume 69, 2024
International Conference on Mobility, Artificial Intelligence and Health (MAIH2024)
|
|
|---|---|---|
| Article Number | 01002 | |
| Number of page(s) | 6 | |
| Section | Artificial Intelligence | |
| DOI | https://doi.org/10.1051/itmconf/20246901002 | |
| Published online | 13 December 2024 | |
Bridging Explainability and Interpretability in AI-driven SCM Projects to Enhance Decision-Making
Université Paris-Saclay, Univ Evry, IMT-BS, LITEM, Evry, France
* Corresponding author: taoufik.el-oualidi@universite-paris-saclay.fr
New AI-based systems implementation in companies is steadily expanding, paving the way for novel organizational sequences. The increasing involvement of end-users has also garnered interest in AI explainability. However, AI explainability continues to be a serious concern, particularly in conventional fields of activity where end-users play an essential role in the large-scale deployment of AI-based solutions. To address this challenge, managing the close relationship between explainability and interpretability deserves particular attention to enable end-users to act and decide with confidence.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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