Explanation in Artificial Intelligence: Insights from the Social Sciences

22 June 2017

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

42 / 1,242 papers shown

Title
Complementary reinforcement learning towards explainable agents J. H. Lee 27 12 0 01 Jan 2019
LEAFAGE: Example-based and Feature importance-based Explanationsfor Black-box ML models Ajaya Adhikari David Tax R. Satta M. Faeth FAtt 28 11 0 21 Dec 2018
Representation, Justification and Explanation in a Value Driven Agent: An Argumentation-Based Approach B. Liao Michael Anderson S. Anderson 20 18 0 13 Dec 2018
The Jiminy Advisor: Moral Agreements Among Stakeholders Based on Norms and Argumentation B. Liao Pere Pardo Marija Slavkovik Leendert van der Torre 22 6 0 11 Dec 2018
Metrics for Explainable AI: Challenges and Prospects R. Hoffman Shane T. Mueller Gary Klein Jordan Litman XAI 15 719 0 11 Dec 2018
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems Sina Mohseni Niloofar Zarei Eric D. Ragan 38 102 0 28 Nov 2018
State of the Art in Fair ML: From Moral Philosophy and Legislation to Fair Classifiers Elias Baumann J. L. Rumberger FaML 29 4 0 20 Nov 2018
Economics of Human-AI Ecosystem: Value Bias and Lost Utility in Multi-Dimensional Gaps Daniel Muller 11 1 0 15 Nov 2018
TED: Teaching AI to Explain its Decisions Michael Hind Dennis L. Wei Murray Campbell Noel Codella Amit Dhurandhar Aleksandra Mojsilović Karthikeyan N. Ramamurthy Kush R. Varshney 13 109 0 12 Nov 2018
Contrastive Explanation: A Structural-Model Approach Tim Miller CML 22 166 0 07 Nov 2018
Progressive Disclosure: Designing for Effective Transparency Aaron Springer Ling Huang 25 16 0 06 Nov 2018
"I had a solid theory before but it's falling apart": Polarizing Effects of Algorithmic Transparency Aaron Springer S. Whittaker 17 6 0 06 Nov 2018
Explaining Explanations in AI Brent Mittelstadt Chris Russell Sandra Wachter XAI 41 661 0 04 Nov 2018
Modeling Stated Preference for Mobility-on-Demand Transit: A Comparison of Machine Learning and Logit Models Xilei Zhao X. Yan Alan Yu Pascal Van Hentenryck 27 24 0 04 Nov 2018
Compositional Attention Networks for Interpretability in Natural Language Question Answering Selvakumar Murugan Suriyadeepan Ramamoorthy Vaidheeswaran Archana Malaikannan Sankarasubbu 22 3 0 30 Oct 2018
Learning with Interpretable Structure from Gated RNN Bo-Jian Hou Zhi-Hua Zhou AI4CE 21 69 0 25 Oct 2018
What can AI do for me: Evaluating Machine Learning Interpretations in Cooperative Play Shi Feng Jordan L. Boyd-Graber HAI 17 128 0 23 Oct 2018
Shedding Light on Black Box Machine Learning Algorithms: Development of an Axiomatic Framework to Assess the Quality of Methods that Explain Individual Predictions Milo Honegger 33 35 0 15 Aug 2018
Techniques for Interpretable Machine Learning Mengnan Du Ninghao Liu Xia Hu FaML 39 1,073 0 31 Jul 2018
Contrastive Explanations for Reinforcement Learning in terms of Expected Consequences J. V. D. Waa J. Diggelen K. Bosch Mark Antonius Neerincx OffRL 31 107 0 23 Jul 2018
Machine Learning Interpretability: A Science rather than a tool Abdul Karim Avinash Mishra M. A. Hakim Newton A. Sattar 6 6 0 18 Jul 2018
Explainable Security Luca Vigano Daniele Magazzeni SILM 21 71 0 11 Jul 2018
A Theory of Diagnostic Interpretation in Supervised Classification Anirban Mukhopadhyay FaML FAtt 6 1 0 26 Jun 2018
xGEMs: Generating Examplars to Explain Black-Box Models Shalmali Joshi Oluwasanmi Koyejo Been Kim Joydeep Ghosh MLAU 25 40 0 22 Jun 2018
Towards a Grounded Dialog Model for Explainable Artificial Intelligence Prashan Madumal Tim Miller F. Vetere L. Sonenberg 18 34 0 21 Jun 2018
Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems Richard J. Tomsett Dave Braines Daniel Harborne Alun D. Preece Supriyo Chakraborty FaML 29 164 0 20 Jun 2018
Agent-Mediated Social Choice Umberto Grandi 9 6 0 19 Jun 2018
Teaching Meaningful Explanations Noel Codella Michael Hind Karthikeyan N. Ramamurthy Murray Campbell Amit Dhurandhar Kush R. Varshney Dennis L. Wei Aleksandra Mojsilović FAtt XAI 15 7 0 29 May 2018
Semantic Explanations of Predictions Freddy Lecue Jiewen Wu FAtt 6 11 0 27 May 2018
Explainable Recommendation: A Survey and New Perspectives Yongfeng Zhang Xu Chen XAI LRM 52 866 0 30 Apr 2018
A review of possible effects of cognitive biases on the interpretation of rule-based machine learning models Tomáš Kliegr Š. Bahník Johannes Furnkranz 17 100 0 09 Apr 2018
The Challenge of Crafting Intelligible Intelligence Daniel S. Weld Gagan Bansal 26 241 0 09 Mar 2018
On Cognitive Preferences and the Plausibility of Rule-based Models Johannes Furnkranz Tomáš Kliegr Heiko Paulheim LRM 17 69 0 04 Mar 2018
Manipulating and Measuring Model Interpretability Forough Poursabzi-Sangdeh D. Goldstein Jake M. Hofman Jennifer Wortman Vaughan Hanna M. Wallach 46 685 0 21 Feb 2018
Hierarchical Expertise-Level Modeling for User Specific Robot-Behavior Explanations S. Sreedharan Siddharth Srivastava S. Kambhampati 22 19 0 19 Feb 2018
Plan Explanations as Model Reconciliation -- An Empirical Study Tathagata Chakraborti S. Sreedharan Sachin Grover S. Kambhampati 27 47 0 03 Feb 2018
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers Fred Hohman Minsuk Kahng Robert S. Pienta Duen Horng Chau OOD HAI 41 536 0 21 Jan 2018
Network Analysis for Explanation Hiroshi Kuwajima Masayuki Tanaka FAtt 11 3 0 07 Dec 2017
Toward Foraging for Understanding of StarCraft Agents: An Empirical Study Sean Penney Jonathan Dodge Claudia Hilderbrand Andrew Anderson Logan Simpson Margaret Burnett 35 33 0 21 Nov 2017
Artificial Intelligence as Structural Estimation: Economic Interpretations of Deep Blue, Bonanza, and AlphaGo Mitsuru Igami 13 34 0 30 Oct 2017
Learning Functional Causal Models with Generative Neural Networks Hugo Jair Escalante Sergio Escalera Xavier Baro Isabelle M Guyon Umut Güçlü Marcel van Gerven CML BDL 22 107 0 15 Sep 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 104 1,505 0 25 Jan 2017