Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs

Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs

To ensure accountability and mitigate harm, it is critical that diverse stakeholders can interrogate black-box automated systems and find information that is understandable, relevant, and useful to them. In this paper, we eschew prior expertise- and role-based categorizations of interpretability...

書誌詳細
主要な著者:	Suresh, Harini, Gomez, Steven R, Nam, Kevin K, Satyanarayan, Arvind
その他の著者:	Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
フォーマット:	論文
言語:	English
出版事項:	Association for Computing Machinery (ACM) 2022
オンライン･アクセス:	https://hdl.handle.net/1721.1/143861

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