Can counterfactual explanations of AI systems’ predictions skew lay users’ causal intuitions about the world? If so, can we correct for that?-Reference-Cited by-同舟云学术

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Can counterfactual explanations of AI systems’ predictions skew lay users’ causal intuitions about the world? If so, can we correct for that?

Published:2022-12 Issue:12 Volume:3 Page:100635
ISSN:2666-3899
Container-title:Patterns
language:en
Short-container-title:Patterns

Author:

Tešić Marko^ORCID,Hahn Ulrike

Funder

Royal Academy of Engineering

Publisher

Elsevier BV

Subject

General Decision Sciences

Reference46 articles.

1. Explainable Artificial Intelligence (XAI) Program,2016

2. Towards a rigorous science of interpretable machine learning;Doshi-Velez;Preprint at arXiv,2017

3. Darpa’s explainable artificial intelligence program;Gunning;AI Mag.,2019

4. Methods for interpreting and understanding deep neural networks;Montavon;Digit. Signal Process.,2018

5. Structuring neural networks for more explainable predictions;Rieger,2018

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2. Ethical issues in explanations of personalized recommender systems;Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization;2023-06-16

3. Argument and explanation;Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences;2023-06-05

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