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pro vyhledávání: '"Rancourt, Fanny"'
Explainability and transparency of AI systems are undeniably important, leading to several research studies and tools addressing them. Existing works fall short of accounting for the diverse stakeholders of the AI supply chain who may differ in their
Externí odkaz:
http://arxiv.org/abs/2405.16311
With the widespread proliferation of AI systems, trust in AI is an important and timely topic to navigate. Researchers so far have largely employed a myopic view of this relationship. In particular, a limited number of relevant trustors (e.g., end-us
Externí odkaz:
http://arxiv.org/abs/2405.16310
Autor:
Maupomé, Diego, Rancourt, Fanny, Soulas, Thomas, Lachance, Alexandre, Meurs, Marie-Jean, Aleksandrova, Desislava, Dufour, Olivier Brochu, Pontes, Igor, Cardon, Rémi, Simard, Michel, Vajjala, Sowmya
This report summarizes the work carried out by the authors during the Twelfth Montreal Industrial Problem Solving Workshop, held at Universit\'e de Montr\'eal in August 2022. The team tackled a problem submitted by CBC/Radio-Canada on the theme of Au
Externí odkaz:
http://arxiv.org/abs/2212.13317
Publikováno v:
In Journal of Statistical Planning and Inference May 2021 212:114-125
Publikováno v:
Stats; Sep2023, Vol. 6 Issue 3, p907-919, 13p