Counterfactual Explanations for Prediction and Diagnosis in XAI

Author:

Dai Xinyue1,Keane Mark T.2,Shalloo Laurence3,Ruelle Elodie3,Byrne Ruth M.J.1

Affiliation:

1. Trinity College Dublin, University of Dublin, Dublin, Ireland

2. University College Dublin, Dublin, Ireland

3. Teagasc Moorepark, Cork, Ireland

Funder

Teagasc Walsh Fellowship PhD Scholarship

Publisher

ACM

Reference45 articles.

1. Verma S. Dickerson J. and Hines K. 2020. Counterfactual explanations for machine learning: A review. arXiv:2010.10596. Retrieved from https://arxiv.org/abs/2010.10596 Verma S. Dickerson J. and Hines K. 2020. Counterfactual explanations for machine learning: A review. arXiv:2010.10596. Retrieved from https://arxiv.org/abs/2010.10596

2. Counterfactual explanations without opening the black box: Automated decisions and the GDPR;Wachter S.;Harvard Journal of Law & Technology,2017

3. Karimi A.H. Barthe G. Schölkopf B. and Valera I. 2020. A survey of algorithmic recourse: definitions formulations solutions and prospects. arXiv:2010.04050. Retrieved from https://arxiv.org/abs/2010.04050 Karimi A.H. Barthe G. Schölkopf B. and Valera I. 2020. A survey of algorithmic recourse: definitions formulations solutions and prospects. arXiv:2010.04050. Retrieved from https://arxiv.org/abs/2010.04050

4. Byrne R. M. J. 2019. Counterfactuals in Explainable Artificial Intelligence (XAI): Evidence from Human Reasoning. In IJCAI 6276--6282. Byrne R. M. J. 2019. Counterfactuals in Explainable Artificial Intelligence (XAI): Evidence from Human Reasoning. In IJCAI 6276--6282.

5. Miller , T. 2019. Explanation in artificial intelligence: Insights from the social sciences. Artificial intelligence, 267 ( 2019 ), 1--38. Miller, T. 2019. Explanation in artificial intelligence: Insights from the social sciences. Artificial intelligence, 267 (2019), 1--38.

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