European Union regulations on algorithmic decision-making and a "right to explanation"

28 June 2016

Seth Flaxman

Papers citing "European Union regulations on algorithmic decision-making and a "right to explanation""

50 / 217 papers shown

Title
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development Aspen K. Hopkins Serena Booth 29 45 0 06 Oct 2021
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 119 357 0 04 Oct 2021
XPROAX-Local explanations for text classification with progressive neighborhood approximation Yi Cai Arthur Zimek Eirini Ntoutsi 25 5 0 30 Sep 2021
Understanding Spending Behavior: Recurrent Neural Network Explanation and Interpretation Charl Maree C. Omlin AI4TS 26 5 0 24 Sep 2021
Self-learn to Explain Siamese Networks Robustly Chao Chen Yifan Shen Guixiang Ma Xiangnan Kong S. Rangarajan Xi Zhang Sihong Xie 48 5 0 15 Sep 2021
Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud Michaela Hardt Xiaoguang Chen Xiaoyi Cheng Michele Donini J. Gelman ... Muhammad Bilal Zafar Sanjiv Ranjan Das Kevin Haas Tyler Hill K. Kenthapadi ELM FaML 36 42 0 07 Sep 2021
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey Richard Dazeley Peter Vamplew Francisco Cruz 32 60 0 20 Aug 2021
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review Florian Tambon Gabriel Laberge Le An Amin Nikanjam Paulina Stevia Nouwou Mindom Y. Pequignot Foutse Khomh G. Antoniol E. Merlo François Laviolette 37 66 0 26 Jul 2021
Model Transferability With Responsive Decision Subjects Yatong Chen Zeyu Tang Kun Zhang Yang Liu 45 10 0 13 Jul 2021
Levels of explainable artificial intelligence for human-aligned conversational explanations Richard Dazeley Peter Vamplew Cameron Foale Charlotte Young Sunil Aryal F. Cruz 30 90 0 07 Jul 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 31 31 0 09 Jun 2021
To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods E. Amparore Alan Perotti P. Bajardi FAtt 33 68 0 01 Jun 2021
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 31 140 0 17 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 34 184 0 15 May 2021
Improving Fairness in Speaker Recognition Gianni Fenu Giacomo Medda Mirko Marras Giacomo Meloni 21 19 0 29 Apr 2021
A First Look: Towards Explainable TextVQA Models via Visual and Textual Explanations Varun Nagaraj Rao Xingjian Zhen K. Hovsepian Mingwei Shen 37 18 0 29 Apr 2021
On the Computational Intelligibility of Boolean Classifiers Gilles Audemard S. Bellart Louenas Bounia F. Koriche Jean-Marie Lagniez Pierre Marquis 24 56 0 13 Apr 2021
Efficient Explanations from Empirical Explainers Robert Schwarzenberg Nils Feldhus Sebastian Möller FAtt 34 9 0 29 Mar 2021
Fairness and Transparency in Recommendation: The Users' Perspective Nasim Sonboli Jessie J. Smith Florencia Cabral Berenfus Robin Burke Casey Fiesler FaML 28 65 0 16 Mar 2021
GRIT: Fast, Interpretable, and Verifiable Goal Recognition with Learned Decision Trees for Autonomous Driving Cillian Brewitt Balint Gyevnar Samuel Garcin Stefano V. Albrecht 18 30 0 10 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 47 176 0 07 Mar 2021
Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms Miguel Á. Carreira-Perpiñán Suryabhan Singh Hada CML AAML 18 33 0 01 Mar 2021
CausalX: Causal Explanations and Block Multilinear Factor Analysis M. Alex O. Vasilescu Eric Kim Xiao-Song Zeng CML 36 10 0 25 Feb 2021
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research Markus Langer Daniel Oster Timo Speith Holger Hermanns Lena Kästner Eva Schmidt Andreas Sesing Kevin Baum XAI 68 415 0 15 Feb 2021
Player-Centered AI for Automatic Game Personalization: Open Problems Jichen Zhu Santiago Ontañón 15 25 0 15 Feb 2021
Characterizing Intersectional Group Fairness with Worst-Case Comparisons A. Ghosh Lea Genuit Mary Reagan FaML 94 51 0 05 Jan 2021
"Brilliant AI Doctor" in Rural China: Tensions and Challenges in AI-Powered CDSS Deployment Dakuo Wang Liuping Wang Zhan Zhang Ding Wang Haiyi Zhu Yvonne Gao Xiangmin Fan Feng Tian 51 144 0 04 Jan 2021
The Three Ghosts of Medical AI: Can the Black-Box Present Deliver? Thomas P. Quinn Stephan Jacobs M. Senadeera Vuong Le S. Coghlan 33 112 0 10 Dec 2020
TimeSHAP: Explaining Recurrent Models through Sequence Perturbations João Bento Pedro Saleiro André F. Cruz Mário A. T. Figueiredo P. Bizarro FAtt AI4TS 24 88 0 30 Nov 2020
Now You See Me (CME): Concept-based Model Extraction Dmitry Kazhdan B. Dimanov M. Jamnik Pietro Lio Adrian Weller 25 72 0 25 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
Landscape of R packages for eXplainable Artificial Intelligence Szymon Maksymiuk Alicja Gosiewska P. Biecek XAI 43 21 0 24 Sep 2020
Model extraction from counterfactual explanations Ulrich Aïvodji Alexandre Bolot Sébastien Gambs MIACV MLAU 33 51 0 03 Sep 2020
Computing Optimal Decision Sets with SAT Jinqiang Yu Alexey Ignatiev Peter Stuckey P. L. Bodic FAtt 22 26 0 29 Jul 2020
Explainability of Intelligent Transportation Systems using Knowledge Compilation: a Traffic Light Controller Case S. Wollenstein-Betech Christian Muise Christos G. Cassandras I. Paschalidis Y. Khazaeni 15 5 0 09 Jul 2020
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 30 627 0 01 Jul 2020
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction Esther Puyol-Antón Chong Chen J. Clough B. Ruijsink B. Sidhu ... M. Elliott Vishal S. Mehta Daniel Rueckert C. Rinaldi A. King 21 32 0 24 Jun 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 37 199 0 22 Jun 2020
Towards Analogy-Based Explanations in Machine Learning Eyke Hüllermeier XAI 11 20 0 23 May 2020
The challenges of deploying artificial intelligence models in a rapidly evolving pandemic Yipeng Hu J. Jacob Geoffrey J. M. Parker D. Hawkes J. Hurst Danail Stoyanov OOD 23 65 0 19 May 2020
Applying Genetic Programming to Improve Interpretability in Machine Learning Models Leonardo Augusto Ferreira F. G. Guimarães Rodrigo C. P. Silva 6 37 0 18 May 2020
The Grammar of Interactive Explanatory Model Analysis Hubert Baniecki Dariusz Parzych P. Biecek 24 44 0 01 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 49 371 0 30 Apr 2020
Learning a Formula of Interpretability to Learn Interpretable Formulas M. Virgolin A. D. Lorenzo Eric Medvet Francesca Randone 25 33 0 23 Apr 2020
Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations Richard Meyes Constantin Waubert de Puiseau Andres Felipe Posada-Moreno Tobias Meisen AI4CE 30 21 0 02 Apr 2020
RelatIF: Identifying Explanatory Training Examples via Relative Influence Elnaz Barshan Marc-Etienne Brunet Gintare Karolina Dziugaite TDI 47 30 0 25 Mar 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 51 82 0 17 Mar 2020
Measuring and improving the quality of visual explanations Agnieszka Grabska-Barwiñska XAI FAtt 24 3 0 14 Mar 2020
Fairness by Explicability and Adversarial SHAP Learning James M. Hickey Pietro G. Di Stefano V. Vasileiou FAtt FedML 33 19 0 11 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 29 213 0 09 Mar 2020