Thank you for providing an exhaustive list of references :)
> Finally, specific to XAI, we're seeing people actually deal with the problem that, well, people aren't really using this stuff!
I am very curious to see which practical interpretability/explainability requirements enter into regulations - on one hand it's hard to imagine a one-size fits all approach, especially for applications incorporating LLMs, but Bordt et al. [1] demonstrate that you can provoke arbitrary feature attributions for a prediction if you can choose post-hoc explanations and parameters freely, making a case that it can't _just_ be left to the model developers either
[1] "Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts", Bordt et al. 2022, https://dl.acm.org/doi/10.1145/3531146.3533153