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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Title
Competition analysis on the over-the-counter credit default swap market L. Abraham 6 0 0 03 Dec 2020
Reviewing the Need for Explainable Artificial Intelligence (xAI) Julie Gerlings Arisa Shollo Ioanna D. Constantiou 22 73 0 02 Dec 2020
Why Did the Robot Cross the Road? A User Study of Explanation in Human-Robot Interaction Zachary Taschdjian 11 0 0 30 Nov 2020
Investigating Human Response, Behaviour, and Preference in Joint-Task Interaction A. Lindsay B. Craenen S. Dalzel-Job Robin L. Hill Ronald P. A. Petrick 11 4 0 27 Nov 2020
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations Wolfgang Stammer P. Schramowski Kristian Kersting FAtt 14 107 0 25 Nov 2020
Model Elicitation through Direct Questioning Sachin Grover David E. Smith S. Kambhampati 15 4 0 24 Nov 2020
The Interpretable Dictionary in Sparse Coding Edward J. Kim Connor Onweller Andrew O'Brien Kathleen F. McCoy 17 1 0 24 Nov 2020
A Bayesian Account of Measures of Interpretability in Human-AI Interaction S. Sreedharan Anagha Kulkarni Tathagata Chakraborti David E. Smith S. Kambhampati 28 10 0 22 Nov 2020
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 53 243 0 21 Nov 2020
Iterative Planning with Plan-Space Explanations: A Tool and User Study Rebecca Eifler Jörg Hoffmann LRM 16 2 0 19 Nov 2020
RADAR-X: An Interactive Mixed Initiative Planning Interface Pairing Contrastive Explanations and Revised Plan Suggestions Karthik Valmeekam S. Sreedharan Sailik Sengupta Subbarao Kambhampati 6 8 0 19 Nov 2020
A Survey on the Explainability of Supervised Machine Learning Nadia Burkart Marco F. Huber FaML XAI 25 753 0 16 Nov 2020
Qualitative Investigation in Explainable Artificial Intelligence: A Bit More Insight from Social Science Adam J. Johs Denise E. Agosto Rosina O. Weber 28 6 0 13 Nov 2020
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End R. Mothilal Divyat Mahajan Chenhao Tan Amit Sharma FAtt CML 32 100 0 10 Nov 2020
Interpretable collaborative data analysis on distributed data A. Imakura Hiroaki Inaba Yukihiko Okada Tetsuya Sakurai FedML 19 26 0 09 Nov 2020
Feature Removal Is a Unifying Principle for Model Explanation Methods Ian Covert Scott M. Lundberg Su-In Lee FAtt 33 33 0 06 Nov 2020
Digital Nudging with Recommender Systems: Survey and Future Directions Mathias Jesse Dietmar Jannach 22 133 0 06 Nov 2020
Necessary and Sufficient Explanations in Abstract Argumentation A. Borg Floris Bex 6 2 0 04 Nov 2020
Towards Personalized Explanation of Robot Path Planning via User Feedback Kayla Boggess Shenghui Chen Lu Feng 17 1 0 01 Nov 2020
Comprehensible Counterfactual Explanation on Kolmogorov-Smirnov Test Zicun Cong Lingyang Chu Yu Yang J. Pei 24 0 0 01 Nov 2020
ExplanationLP: Abductive Reasoning for Explainable Science Question Answering Mokanarangan Thayaparan Marco Valentino André Freitas LRM 28 9 0 25 Oct 2020
Measuring Association Between Labels and Free-Text Rationales Sarah Wiegreffe Ana Marasović Noah A. Smith 282 172 0 24 Oct 2020
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization Judy Borowski Roland S. Zimmermann Judith Schepers Robert Geirhos Thomas S. A. Wallis Matthias Bethge Wieland Brendel FAtt 47 7 0 23 Oct 2020
Model Interpretability through the Lens of Computational Complexity Pablo Barceló Mikaël Monet Jorge A. Pérez Bernardo Subercaseaux 132 94 0 23 Oct 2020
On Explaining Decision Trees Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 26 85 0 21 Oct 2020
Axiom Learning and Belief Tracing for Transparent Decision Making in Robotics Tiago Mota Mohan Sridharan 21 5 0 20 Oct 2020
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review Sahil Verma Varich Boonsanong Minh Hoang Keegan E. Hines John P. Dickerson Chirag Shah CML 28 164 0 20 Oct 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 28 396 0 19 Oct 2020
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making Charvi Rastogi Yunfeng Zhang Dennis L. Wei Kush R. Varshney Amit Dhurandhar Richard J. Tomsett HAI 32 109 0 15 Oct 2020
Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense Graphs Ana Marasović Chandra Bhagavatula J. S. Park Ronan Le Bras Noah A. Smith Yejin Choi ReLM LRM 20 62 0 15 Oct 2020
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI Alon Jacovi Ana Marasović Tim Miller Yoav Goldberg 262 428 0 15 Oct 2020
The elephant in the interpretability room: Why use attention as explanation when we have saliency methods? Jasmijn Bastings Katja Filippova XAI LRM 64 175 0 12 Oct 2020
Towards a Conversational Measure of Trust Mengyao Li Areen Alsaid Sofia I. Noejovich E. V. Cross John D. Lee HILM 6 4 0 10 Oct 2020
A Series of Unfortunate Counterfactual Events: the Role of Time in Counterfactual Explanations Andrea Ferrario M. Loi 25 5 0 09 Oct 2020
Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning Julia B. Nakhleh M. G. Fernández-Godino M. Grosskopf B. Wilson J. Kline G. Srinivasan 29 7 0 08 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Amir-Hossein Karimi Gilles Barthe Bernhard Schölkopf Isabel Valera FaML 19 172 0 08 Oct 2020
Simplifying the explanation of deep neural networks with sufficient and necessary feature-sets: case of text classification Florentin Flambeau Jiechieu Kameni Norbert Tsopzé XAI FAtt MedIm 22 1 0 08 Oct 2020
Interpretable Sequence Classification via Discrete Optimization Maayan Shvo Andrew C. Li Rodrigo Toro Icarte Sheila A. McIlraith 10 18 0 06 Oct 2020
Efficient computation of contrastive explanations André Artelt Barbara Hammer 13 9 0 06 Oct 2020
Explanation Ontology: A Model of Explanations for User-Centered AI Shruthi Chari Oshani Seneviratne Daniel Gruen Morgan Foreman Amar K. Das D. McGuinness XAI 10 52 0 04 Oct 2020
A Survey on Explainability in Machine Reading Comprehension Mokanarangan Thayaparan Marco Valentino André Freitas FaML 25 50 0 01 Oct 2020
Explainable AI without Interpretable Model Kary Framling ELM 6 7 0 29 Sep 2020
Instance-based Counterfactual Explanations for Time Series Classification Eoin Delaney Derek Greene Mark T. Keane CML AI4TS 21 89 0 28 Sep 2020
Disentangled Neural Architecture Search Xinyue Zheng Peng Wang Qigang Wang Zhongchao Shi AI4CE 35 4 0 24 Sep 2020
Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing Nijat Mehdiyev Peter Fettke 21 11 0 22 Sep 2020
ALICE: Active Learning with Contrastive Natural Language Explanations Weixin Liang James Zou Zhou Yu VLM 32 50 0 22 Sep 2020
Survey of explainable machine learning with visual and granular methods beyond quasi-explanations Boris Kovalerchuk M. Ahmad University of Washington Tacoma 8 42 0 21 Sep 2020
Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects Falco J. Bargagli-Stoffi Riccardo Cadei Kwonsang Lee Francesca Dominici CML 20 16 0 18 Sep 2020
Principles and Practice of Explainable Machine Learning Vaishak Belle I. Papantonis FaML 26 437 0 18 Sep 2020
Addressing Cognitive Biases in Augmented Business Decision Systems Thomas Baudel Manon Verbockhaven Guillaume Roy Victoire Cousergue Rida Laarach 30 3 0 17 Sep 2020