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Thread: Miscellaneous

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    Book "Explainable AI: Interpreting, Explaining and Visualizing Deep Learning"

    Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Müller

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    "XAI—Explainable artificial intelligence"

    by David Gunning, Mark Stefik, Jaesik Choi, Timothy Miller, Simone Stumpf, Guang-Zhong Yang
    December 18, 2019

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    Article "UX defines chasm between explainable vs. interpretable AI"
    From deep learning to simple code, all algorithms should be transparent. The frameworks of AI interpretability and explainability aim to make machine learning understandable to humans.

    by George Lawton
    December 24, 2019

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    Article "Why asking an AI to explain itself can make things worse"
    Creating neural networks that are more transparent can lead us to over-trust them. The solution might be to change how they explain themselves.

    by Douglas Heaven
    January 29, 2020

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