AI KR, explainabiilty, state of the art

This CG was started six years ago, as machine learning was become
unintelligible a risk and a threat

The mission  of this CG has been - and still is - to monitor the state of
the art in AI (what is going on) and
leverage  KR and structural engineering methods to support this
understanding

It has been proposed that without knowledge representation. there cannot be
AI explainability
https://lists.w3.org/Archives/Public/semantic-web/2019Aug/0048.html

Very useful stato of the art work being done here, that pretty much
contributes to this mission

Meike Nauta, Jan Trienes, Shreyasi Pathak, Elisa Nguyen, Michelle
Peters, Yasmin Schmitt, Jörg Schlötterer, Maurice van Keulen, and
Christin Seifert. 2023. From Anecdotal Evidence to Quantitative
Evaluation Methods: A Systematic Review on Evaluating Explainable AI.
ACM Comput. Surv. 55, 13s, Article 295 (December 2023), 42 pages.
https://doi.org/10.1145/3583558

https://dl.acm.org/doi/pdf/10.1145/3583558

Let's continue to explore this important direction