Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions
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| Format: | Preprint |
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2026
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| author | Afroogh, Saleh Ahmed, Syed Ishtiaque Ahrweiler, Petra Alvarez-Melis, David Arief, Mansur Maturidi Barakova, Emilia Bargagli-Stoffi, Falco J. Biyik, Erdem Chen, Hanjie Chen, Xiang 'Anthony' Clements, Robert Alan Crockett, Keeley Dhurandhar, Amit Dogan, Fethiye Irmak Dollinger, Mollie Eslami, Motahhare Faisal, Aldo A Farahi, Arya Pradier, Melanie F. Gabriel, Saadia Garcia-Olano, Diego Ghassemi, Marzyeh Ghosh, Shaona Gunes, Hatice Hajiramezanali, Ehsan Haufe, Stefan Huang, Biwei Hwang, Angel Islam, Md Tauhidul Jiao, Junfeng Karimi, Amir-Hossein Kazeminasab, Saber Kuzminykh, Anastasia La Cava, William Lim, Brian Y. Liu, Xiaofeng Mofrad, Mohammad R. K. Parrish, Alicia Perez-Ortiz, Maria Raj, Shriti Swayamdipta, Swabha Talebi, Salmonn Varshney, Kush R. Vorvoreanu, Mihaela Weng, Lily Xiang, Alice Xu, Yiming Zhao, Ding Zhao, Jieyu |
| author_facet | Afroogh, Saleh Ahmed, Syed Ishtiaque Ahrweiler, Petra Alvarez-Melis, David Arief, Mansur Maturidi Barakova, Emilia Bargagli-Stoffi, Falco J. Biyik, Erdem Chen, Hanjie Chen, Xiang 'Anthony' Clements, Robert Alan Crockett, Keeley Dhurandhar, Amit Dogan, Fethiye Irmak Dollinger, Mollie Eslami, Motahhare Faisal, Aldo A Farahi, Arya Pradier, Melanie F. Gabriel, Saadia Garcia-Olano, Diego Ghassemi, Marzyeh Ghosh, Shaona Gunes, Hatice Hajiramezanali, Ehsan Haufe, Stefan Huang, Biwei Hwang, Angel Islam, Md Tauhidul Jiao, Junfeng Karimi, Amir-Hossein Kazeminasab, Saber Kuzminykh, Anastasia La Cava, William Lim, Brian Y. Liu, Xiaofeng Mofrad, Mohammad R. K. Parrish, Alicia Perez-Ortiz, Maria Raj, Shriti Swayamdipta, Swabha Talebi, Salmonn Varshney, Kush R. Vorvoreanu, Mihaela Weng, Lily Xiang, Alice Xu, Yiming Zhao, Ding Zhao, Jieyu |
| contents | This study provides a cross-disciplinary examination of Explainable Artificial Intelligence (XAI) approaches-focusing on deep neural networks (DNNs) and large language models (LLMs)-and identifies empirical and conceptual limitations in current XAI. We discuss critical symptoms that stem from deeper root causes (i.e., two paradoxes, two conceptual confusions, and five false assumptions). These fundamental problems within the current XAI research field reveal three insights: experimentally, XAI exhibits significant flaws; conceptually, it is paradoxical; and pragmatically, further attempts to reform the paradoxical XAI might exacerbate its confusion-demanding fundamental shifts and new research directions. To move beyond XAI's limitations, we propose a four-pronged synthesized paradigm shift toward reliable and certified AI development. These four components include: verification-focused Interactive AI (IAI) to establish scientific community protocols for certifying AI system performance rather than attempting post-hoc explanations, AI Epistemology for rigorous scientific foundations, User-Sensible AI to create context-aware systems tailored to specific user communities, and Model-Centered Interpretability for faithful technical analysis-together offering comprehensive post-XAI research directions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_24176 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions Afroogh, Saleh Ahmed, Syed Ishtiaque Ahrweiler, Petra Alvarez-Melis, David Arief, Mansur Maturidi Barakova, Emilia Bargagli-Stoffi, Falco J. Biyik, Erdem Chen, Hanjie Chen, Xiang 'Anthony' Clements, Robert Alan Crockett, Keeley Dhurandhar, Amit Dogan, Fethiye Irmak Dollinger, Mollie Eslami, Motahhare Faisal, Aldo A Farahi, Arya Pradier, Melanie F. Gabriel, Saadia Garcia-Olano, Diego Ghassemi, Marzyeh Ghosh, Shaona Gunes, Hatice Hajiramezanali, Ehsan Haufe, Stefan Huang, Biwei Hwang, Angel Islam, Md Tauhidul Jiao, Junfeng Karimi, Amir-Hossein Kazeminasab, Saber Kuzminykh, Anastasia La Cava, William Lim, Brian Y. Liu, Xiaofeng Mofrad, Mohammad R. K. Parrish, Alicia Perez-Ortiz, Maria Raj, Shriti Swayamdipta, Swabha Talebi, Salmonn Varshney, Kush R. Vorvoreanu, Mihaela Weng, Lily Xiang, Alice Xu, Yiming Zhao, Ding Zhao, Jieyu Computers and Society This study provides a cross-disciplinary examination of Explainable Artificial Intelligence (XAI) approaches-focusing on deep neural networks (DNNs) and large language models (LLMs)-and identifies empirical and conceptual limitations in current XAI. We discuss critical symptoms that stem from deeper root causes (i.e., two paradoxes, two conceptual confusions, and five false assumptions). These fundamental problems within the current XAI research field reveal three insights: experimentally, XAI exhibits significant flaws; conceptually, it is paradoxical; and pragmatically, further attempts to reform the paradoxical XAI might exacerbate its confusion-demanding fundamental shifts and new research directions. To move beyond XAI's limitations, we propose a four-pronged synthesized paradigm shift toward reliable and certified AI development. These four components include: verification-focused Interactive AI (IAI) to establish scientific community protocols for certifying AI system performance rather than attempting post-hoc explanations, AI Epistemology for rigorous scientific foundations, User-Sensible AI to create context-aware systems tailored to specific user communities, and Model-Centered Interpretability for faithful technical analysis-together offering comprehensive post-XAI research directions. |
| title | Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2602.24176 |