Disagreement of Explainers

[vinitra]

Hi Christoph -- great work with the recent additions to the book; I really liked the neural net chapters. I recommend this book to everyone. :)

I might have missed it, but I think there's a great space to talk about recent studies in disagreement for black box explainers at the end of Chapter 9. I had a recent publication on this in the XAI for education space. Around the same time, there was a great ArXiv preprint by a team from Harvard / MIT / CMU and Drexel that discusses the more general implications on different popular datasets, also with a data scientist user study.

Of course, this 2019 Nature article asking us to use interpretable models instead of explainability methods from Cynthia Rudin is a predecessor and a classic.

Thanks,
Vinitra

[christophM]

Hi Vinitra Thanks a lot for sharing your paper(s), and also thank you for your nice words. I will take a look. Best, Christoph Am Mi., 21. Sept. 2022 um 13:20 Uhr schrieb Vinitra Swamy < ***@***.***>:

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Hi Christoph -- great work with the recent additions to the book; I really liked the neural net chapters. As I wrote you a few years ago, I recommend this book to any interested students working in trustworthy AI. :) I might have missed it, but I think there's a great space to talk about recent studies in disagreement for black box explainers at the end of Chapter 9. I had a recent publication on this in the XAI for education space <https://educationaldatamining.org/edm2022/proceedings/2022.EDM-long-papers.9/2022.EDM-long-papers.9.pdf>. Around the same time, there was a great ArXiv preprint by a team from Harvard / MIT / CMU and Drexel <https://arxiv.org/abs/2202.01602> that discusses the more general implications on different popular datasets, also with a data scientist user study. Of course, this 2019 Nature article asking us to use interpretable models instead of explainability methods from Cynthia Rudin <https://www.nature.com/articles/s42256-019-0048-x> is a predecessor and a classic. Thanks, Vinitra — Reply to this email directly, view it on GitHub <#347>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAMOOZBVVQ3JK252FRCQUGDV7LVPLANCNFSM6AAAAAAQR632MQ> . You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

-- Christoph Molnar https://christophmolnar.com/ Machine Learning Expert | Author of Interpretable Machine Learning <https://bit.ly/3K3AV1y> and Modeling Mindsets <https://leanpub.com/modeling-mindsets>