"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans

14 January 2020

Papers citing ""Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans"

37 / 87 papers shown

Title
Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations Yao Rong Tobias Leemann Thai-trang Nguyen Lisa Fiedler Peizhu Qian Vaibhav Unhelkar Tina Seidel Gjergji Kasneci Enkelejda Kasneci ELM 25 91 0 20 Oct 2022
Learning When to Advise Human Decision Makers Gali Noti Yiling Chen 39 15 0 27 Sep 2022
Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making Jakob Schoeffer Maria De-Arteaga Niklas Kuehl FaML 28 45 0 23 Sep 2022
Sample Efficient Learning of Predictors that Complement Humans Mohammad-Amin Charusaie Hussein Mozannar David Sontag Samira Samadi 23 31 0 19 Jul 2022
Argumentative Explanations for Pattern-Based Text Classifiers Piyawat Lertvittayakumjorn Francesca Toni 27 4 0 22 May 2022
A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making Max Schemmer Patrick Hemmer Maximilian Nitsche Niklas Kühl Michael Vossing 19 55 0 10 May 2022
On the Effect of Information Asymmetry in Human-AI Teams Patrick Hemmer Max Schemmer Niklas Kühl Michael Vossing G. Satzger 6 19 0 03 May 2022
Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation Vivian Lai Samuel Carton Rajat Bhatnagar Vera Liao Yunfeng Zhang Chenhao Tan 18 129 0 25 Apr 2022
On the Influence of Explainable AI on Automation Bias Max Schemmer Niklas Kühl Carina Benz G. Satzger 20 28 0 19 Apr 2022
Should I Follow AI-based Advice? Measuring Appropriate Reliance in Human-AI Decision-Making Max Schemmer Patrick Hemmer Niklas Kühl Carina Benz G. Satzger 12 54 0 14 Apr 2022
Towards Explainable Evaluation Metrics for Natural Language Generation Christoph Leiter Piyawat Lertvittayakumjorn M. Fomicheva Wei-Ye Zhao Yang Gao Steffen Eger AAML ELM 22 20 0 21 Mar 2022
Do People Engage Cognitively with AI? Impact of AI Assistance on Incidental Learning Krzysztof Z. Gajos Lena Mamykina 14 99 0 11 Feb 2022
Machine Explanations and Human Understanding Chacha Chen Shi Feng Amit Sharma Chenhao Tan 19 24 0 08 Feb 2022
Rethinking Explainability as a Dialogue: A Practitioner's Perspective Himabindu Lakkaraju Dylan Slack Yuxin Chen Chenhao Tan Sameer Singh LRM 13 64 0 03 Feb 2022
Human-AI Collaboration for UX Evaluation: Effects of Explanation and Synchronization Mingming Fan Xianyou Yang Tsz Tung Yu Vera Q. Liao J. Zhao 24 1 0 23 Dec 2021
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies Vivian Lai Chacha Chen Q. V. Liao Alison Smith-Renner Chenhao Tan 18 186 0 21 Dec 2021
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations Siddhant Arora Danish Pruthi Norman M. Sadeh William W. Cohen Zachary Chase Lipton Graham Neubig FAtt 30 38 0 17 Dec 2021
Teaching Humans When To Defer to a Classifier via Exemplars Hussein Mozannar Arvindmani Satyanarayan David Sontag 26 43 0 22 Nov 2021
Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Work Through Explainable Artificial Intelligence Max Schemmer Niklas Kühl G. Satzger 16 13 0 28 Sep 2021
Decision-Focused Summarization Chao-Chun Hsu Chenhao Tan 23 16 0 14 Sep 2021
On the Diversity and Limits of Human Explanations Chenhao Tan 16 31 0 22 Jun 2021
The effectiveness of feature attribution methods and its correlation with automatic evaluation scores Giang Nguyen Daeyoung Kim Anh Totti Nguyen FAtt 10 86 0 31 May 2021
Explanation-Based Human Debugging of NLP Models: A Survey Piyawat Lertvittayakumjorn Francesca Toni LRM 28 79 0 30 Apr 2021
Misinfo Reaction Frames: Reasoning about Readers' Reactions to News Headlines Saadia Gabriel Skyler Hallinan Maarten Sap Pemi Nguyen Franziska Roesner Eunsol Choi Yejin Choi 16 41 0 18 Apr 2021
Question-Driven Design Process for Explainable AI User Experiences Q. V. Liao Milena Pribić Jaesik Han Sarah Miller Daby M. Sow 15 52 0 08 Apr 2021
To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making Zana Buçinca M. Malaya Krzysztof Z. Gajos 20 299 0 19 Feb 2021
RECAST: Enabling User Recourse and Interpretability of Toxicity Detection Models with Interactive Visualization Austin P. Wright Omar Shaikh Haekyu Park Will Epperson Muhammed Ahmed Stephane Pinel Duen Horng Chau Diyi Yang 17 21 0 08 Feb 2021
EUCA: the End-User-Centered Explainable AI Framework Weina Jin Jianyu Fan D. Gromala Philippe Pasquier Ghassan Hamarneh 40 24 0 04 Feb 2021
Show or Suppress? Managing Input Uncertainty in Machine Learning Model Explanations Danding Wang Wencan Zhang Brian Y. Lim FAtt 11 22 0 23 Jan 2021
Understanding the Effect of Out-of-distribution Examples and Interactive Explanations on Human-AI Decision Making Han Liu Vivian Lai Chenhao Tan 17 116 0 13 Jan 2021
Expanding Explainability: Towards Social Transparency in AI systems Upol Ehsan Q. V. Liao Michael J. Muller Mark O. Riedl Justin D. Weisz 43 390 0 12 Jan 2021
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 27 108 0 15 Oct 2020
Evaluating and Characterizing Human Rationales Samuel Carton Anirudh Rathore Chenhao Tan 6 48 0 09 Oct 2020
Are Visual Explanations Useful? A Case Study in Model-in-the-Loop Prediction Eric Chu D. Roy Jacob Andreas FAtt LRM 6 71 0 23 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 23 575 0 26 Jun 2020
Harnessing Explanations to Bridge AI and Humans Vivian Lai Samuel Carton Chenhao Tan 6 5 0 16 Mar 2020
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,681 0 28 Feb 2017