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Explanation in Artificial Intelligence: Insights from the Social Sciences

22 June 2017

Papers citing "Explanation in Artificial Intelligence: Insights from the Social Sciences"

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How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural NetworksIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020 Thomas Fel David Vigouroux Rémi Cadène Thomas Serre XAI FAtt 365 34 0 07 Sep 2020
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process MonitoringStudies in Computational Intelligence (SCI), 2020 Nijat Mehdiyev Peter Fettke AI4TS 210 63 0 04 Sep 2020
Why should I not follow you? Reasons For and Reasons Against in Responsible Recommender Systems G. Polleti Douglas Luan de Souza Fabio Gagliardi Cozman 127 1 0 03 Sep 2020
Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems Jeremy E. Block Eric D. Ragan 120 8 0 02 Sep 2020
Machine Reasoning Explainability K. Čyras R. Badrinath S. Mohalik A. Mujumdar Alexandros Nikou Alessandro Previti Vaishnavi Sundararajan Aneta Vulgarakis Feljan LRM 275 13 0 01 Sep 2020
Counterfactual Explanations for Machine Learning on Multivariate Time Series Data E. Ates Burak Aksar V. Leung A. Coskun AI4TS 256 90 0 25 Aug 2020
A Survey of Knowledge-based Sequential Decision Making under Uncertainty Shiqi Zhang Mohan Sridharan 220 16 0 19 Aug 2020
DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models Furui Cheng Yao Ming Huamin Qu CML HAI 122 122 0 19 Aug 2020
Mediating Community-AI Interaction through Situated Explanation: The Case of AI-Led Moderation Yubo Kou Xinning Gui 95 45 0 19 Aug 2020
Tackling COVID-19 through Responsible AI Innovation: Five Steps in the Right Direction David Leslie 298 73 0 15 Aug 2020
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay Sasha Rubin Thomas Gerspacher Martin C. Cooper Alexey Ignatiev Nina Narodytska FAtt 229 69 0 13 Aug 2020
Bias and Discrimination in AI: a cross-disciplinary perspectiveIEEE technology & society magazine (TS), 2020 Xavier Ferrer Tom van Nuenen Jose Such Mark Coté Natalia Criado FaML 152 192 0 11 Aug 2020
Making Sense of CNNs: Interpreting Deep Representations & Their Invariances with INNs Robin Rombach Patrick Esser Bjorn Ommer 147 18 0 04 Aug 2020
Exploiting Game Theory for Analysing Justifications Simon Marynissen B. Bogaerts M. Denecker 58 4 0 04 Aug 2020
IntroVAC: Introspective Variational Classifiers for Learning Interpretable Latent Subspaces Marco Maggipinto M. Terzi Gian Antonio Susto 249 1 0 03 Aug 2020
A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution A. Khademi Vasant Honavar CML 126 9 0 01 Aug 2020
The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategiesJournal of Biomedical Informatics (JBI), 2020 A. Markus J. Kors P. Rijnbeek 233 569 0 31 Jul 2020
Neural Temporal Point Processes For Modelling Electronic Health Records Joseph Enguehard Dan Busbridge Adam James Bozson Claire Woodcock Nils Y. Hammerla 218 51 0 27 Jul 2020
Interpretabilité des modèles : état des lieux des méthodes et application à lássurance Dimitri Delcaillau A. Ly Franck Vermet Alizé Papp 76 1 0 25 Jul 2020
Joint Mind Modeling for Explanation Generation in Complex Human-Robot Collaborative TasksIEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2020 Xiaofeng Gao Ran Gong Yizhou Zhao Shu Wang Tianmin Shu Song-Chun Zhu 173 42 0 24 Jul 2020
Memory networks for consumer protection:unfairness exposed Federico Ruggeri F. Lagioia Marco Lippi Paolo Torroni 109 0 0 24 Jul 2020
Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context Ehsan Toreini Mhairi Aitken Kovila P. L. Coopamootoo Karen Elliott Vladimiro González-Zelaya P. Missier Magdalene Ng Aad van Moorsel 286 19 0 17 Jul 2020
On quantitative aspects of model interpretability An-phi Nguyen María Rodríguez Martínez 180 130 0 15 Jul 2020
Cause vs. Effect in Context-Sensitive Prediction of Business Process InstancesInformation Systems (Inf. Syst.), 2020 Jens Brunk M. Stierle Leon Papke K. Revoredo Martin Matzner J. Becker 120 25 0 15 Jul 2020
XAlgo: a Design Probe of Explaining Algorithms' Internal States via Question-Answering Juan Rebanal Yuqi Tang Jordan Combitsis Xiang Ánthony' Chen 162 3 0 14 Jul 2020
Machine Learning Explainability for External Stakeholders Umang Bhatt Mckane Andrus Adrian Weller Alice Xiang FaML SILM 147 63 0 10 Jul 2020
Model Distillation for Revenue Optimization: Interpretable Personalized Pricing Max Biggs Wei-Ju Sun M. Ettl 289 41 0 03 Jul 2020
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 321 719 0 01 Jul 2020
Unifying Model Explainability and Robustness via Machine-Checkable Concepts Vedant Nanda Till Speicher John P. Dickerson Krishna P. Gummadi Muhammad Bilal Zafar AAML 163 4 0 01 Jul 2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance Gagan Bansal Tongshuang Wu Joyce Zhou Raymond Fok Besmira Nushi Ece Kamar Marco Tulio Ribeiro Daniel S. Weld 367 718 0 26 Jun 2020
Background Knowledge Injection for Interpretable Sequence Classification S. Gsponer Luca Costabello Chan Le Van Sumit Pai Christophe Guéret Georgiana Ifrim Freddy Lecue 118 1 0 25 Jun 2020
Generative causal explanations of black-box classifiersNeural Information Processing Systems (NeurIPS), 2020 Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 265 76 0 24 Jun 2020
Explainable robotic systems: Understanding goal-driven actions in a reinforcement learning scenario Francisco Cruz Richard Dazeley Peter Vamplew Ithan Moreira 277 45 0 24 Jun 2020
Online Handbook of Argumentation for AI: Volume 1 Ohaai Collaboration Federico Castagna Federico Castagna T. Kampik Atefeh Keshavarzi Zafarghandi Mickael Lafages ... Samy Sá Stefan Sarkadi Joseph Singleton Kenneth Skiba A. Xydis 162 1 0 22 Jun 2020
Non-repudiable provenance for clinical decision support systems Elliot Fairweather Rudolf Wittner Martin Chapman P. Holub V. Curcin 37 8 0 19 Jun 2020
Does Explainable Artificial Intelligence Improve Human Decision-Making? Y. Alufaisan L. Marusich J. Bakdash Yan Zhou Murat Kantarcioglu XAI 206 115 0 19 Jun 2020
How does this interaction affect me? Interpretable attribution for feature interactions Michael Tsang Sirisha Rambhatla Yan Liu FAtt 190 97 0 19 Jun 2020
Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey Arun Das P. Rad XAI 386 696 0 16 Jun 2020
Contestable Black Boxes Andrea Aler Tubella Andreas Theodorou Virginia Dignum Loizos Michael 91 17 0 09 Jun 2020
Interpretable Classification of Bacterial Raman Spectra with Knockoff Wavelets Charmaine Chia Matteo Sesia Chi-Sing Ho S. Jeffrey J. Dionne Emmanuel J. Candès R. Howe 218 6 0 08 Jun 2020
From Checking to Inference: Actual Causality Computations as Optimization Problems Amjad Ibrahim A. Pretschner LRM 171 15 0 05 Jun 2020
Local Interpretability of Calibrated Prediction Models: A Case of Type 2 Diabetes Mellitus Screening Test Simon Kocbek Primož Kocbek Leona Cilar Gregor Stiglic 101 2 0 02 Jun 2020
Aligning Faithful Interpretations with their Social AttributionTransactions of the Association for Computational Linguistics (TACL), 2020 Alon Jacovi Yoav Goldberg 275 111 0 01 Jun 2020
Explanations of Black-Box Model Predictions by Contextual Importance and Utility S. Anjomshoae Kary Främling A. Najjar 154 38 0 30 May 2020
Explainable Artificial Intelligence: a Systematic Review Giulia Vilone Luca Longo XAI 551 300 0 29 May 2020
A Performance-Explainability Framework to Benchmark Machine Learning Methods: Application to Multivariate Time Series Classifiers Kevin Fauvel Véronique Masson Elisa Fromont AI4TS 255 19 0 29 May 2020
Who is this Explanation for? Human Intelligence and Knowledge Graphs for eXplainable AI I. Celino 115 6 0 27 May 2020
Good Counterfactuals and Where to Find Them: A Case-Based Technique for Generating Counterfactuals for Explainable AI (XAI)International Conference on Case-Based Reasoning (ICCBR), 2020 Mark T. Keane Barry Smyth CML 168 162 0 26 May 2020
The Skincare project, an interactive deep learning system for differential diagnosis of malignant skin lesions. Technical Report Daniel Sonntag Fabrizio Nunnari H. Profitlich 128 12 0 19 May 2020
Local and Global Explanations of Agent Behavior: Integrating Strategy Summaries with Saliency Maps Tobias Huber Katharina Weitz Elisabeth André Ofra Amir FAtt 300 71 0 18 May 2020