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Why Is the Current XAI Not Meeting the Expectations?

Published: 17 November 2023 Publication History

Abstract

Seeking better explanations for how algorithmic decisions are made.

References

[1]
Bordt, S. et al. Post-hoc explanations fail to achieve their purpose in adversarial contexts. (2022); arXiv:2201.10295.
[2]
de Bruijn, H. et al. The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making. Government Information Quarterly 39, 2 (2022), 101666
[3]
Carroll, J.M. Why should humans trust AI? Interactions 29, 4 (2022), 73--77.
[4]
Caruana, R. and Nori, H. Why data scientists prefer glassbox machine learning: Algorithms, differential privacy, editing and bias mitigation. In Proceedings of SIGKDD. (2022).
[5]
Fischer, G. et al. Meta-design: a manifesto for end-user development. Commun. ACM 47, 9 (Sept. 2004), 33--37.
[6]
Ghassemi, M. et al. The false hope of current approaches to explainable artificial intelligence in health care. The Lancet Digital Health 3, 11 (2021), e745--e750.
[7]
Habayeb, A. Explainable AI isn't enough; We need understandable AI. (Feb. 16, 2022); https://bit.ly/3RvrOgW.
[8]
Kahn, J. What's wrong with "explainable A.I." (Mar. 22, 2022); https://bit.ly/45StDcp.
[9]
Krishna, S. et al. The disagreement problem in explainable machine learning: A practitioner's perspective. (2022); arXiv preprint arXiv:2202.01602.
[10]
Lengerich, B.J. et al. Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case study. Journal of Biomedical Informatics 130, (June 2022), 104086.
[11]
Liao, Q.V. et al. Questioning the AI: informing design practices for explainable AI user experiences. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. (Apr. 2020), 1--15.
[12]
Miller, T. Explanation in artificial intelligence: Insights from the social sciences. Artificial Intelligence 267, (2019), 1--38.
[13]
Munn, L. The uselessness of AI ethics. AI and Ethics. (2022), 1--9.
[14]
Rittel, H.W. and Webber, M.M. Dilemmas in a general theory of planning. Policy Sciences 4, 2 (Feb. 1973), 155--169.
[15]
Rudin, C. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence 1, 5 (2019), 206--215.
[16]
Wang, C. et al. In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction. (Mar. 2022); https://arxiv.org/abs/2005.04176.

Cited By

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  • (2024)Adaptive XAI: Towards Intelligent Interfaces for Tailored AI ExplanationsCompanion Proceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640544.3645253(119-121)Online publication date: 18-Mar-2024
  • (2024)Re-examining the chatBot Usability Scale (BUS-11) to assess user experience with customer relationship management chatbotsPersonal and Ubiquitous Computing10.1007/s00779-024-01834-4Online publication date: 5-Nov-2024

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Published In

cover image Communications of the ACM
Communications of the ACM  Volume 66, Issue 12
December 2023
88 pages
ISSN:0001-0782
EISSN:1557-7317
DOI:10.1145/3633437
  • Editor:
  • James Larus
Issue’s Table of Contents
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 November 2023
Published in CACM Volume 66, Issue 12

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Cited By

View all
  • (2024)Adaptive XAI: Towards Intelligent Interfaces for Tailored AI ExplanationsCompanion Proceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640544.3645253(119-121)Online publication date: 18-Mar-2024
  • (2024)Re-examining the chatBot Usability Scale (BUS-11) to assess user experience with customer relationship management chatbotsPersonal and Ubiquitous Computing10.1007/s00779-024-01834-4Online publication date: 5-Nov-2024

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