Understanding the impact of explanations on advice-taking: a user study for AI-based clinical Decision Support Systems

Author:

Panigutti Cecilia1,Beretta Andrea2,Giannotti Fosca3,Pedreschi Dino4

Affiliation:

1. Scuola Normale Superiore, Italy and Computer Science, University of Pisa, Italy

2. ISTI, CNR - Italian National Research Council, Italy

3. CNR - Italian National Research Council, Italy and Scuola Normale Superiore, Italy

4. Computer Science, University of Pisa, Italy

Funder

European Commission

Publisher

ACM

Reference85 articles.

1. European Commission 2018. EU General Data Protection Regulation. European Commission. https://ec.europa.eu/commission/sites/beta-political/files/data-protection-factsheet-changes_en.pdf European Commission 2018. EU General Data Protection Regulation. European Commission. https://ec.europa.eu/commission/sites/beta-political/files/data-protection-factsheet-changes_en.pdf

2. Barbara D Adams Lora E Bruyn Sébastien Houde Paul Angelopoulos Kim Iwasa-Madge and Carol McCann. 2003. Trust in automated systems. Ministry of National Defence(2003). Barbara D Adams Lora E Bruyn Sébastien Houde Paul Angelopoulos Kim Iwasa-Madge and Carol McCann. 2003. Trust in automated systems. Ministry of National Defence(2003).

3. Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review

4. Vijay Arya Rachel KE Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind Samuel C Hoffman Stephanie Houde Q Vera Liao Ronny Luss Aleksandra Mojsilović 2019. One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques. arXiv preprint arXiv:1909.03012(2019). Vijay Arya Rachel KE Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind Samuel C Hoffman Stephanie Houde Q Vera Liao Ronny Luss Aleksandra Mojsilović 2019. One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques. arXiv preprint arXiv:1909.03012(2019).

5. Alina Jade Barnett Fides Regina Schwartz Chaofan Tao Chaofan Chen Yinhao Ren Joseph Y Lo and Cynthia Rudin. 2021. A case-based interpretable deep learning model for classification of mass lesions in digital mammography. Nature Machine Intelligence(2021) 1–10. Alina Jade Barnett Fides Regina Schwartz Chaofan Tao Chaofan Chen Yinhao Ren Joseph Y Lo and Cynthia Rudin. 2021. A case-based interpretable deep learning model for classification of mass lesions in digital mammography. Nature Machine Intelligence(2021) 1–10.

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