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Question-Driven Design Process for Explainable AI User Experiences

8 April 2021

Papers citing "Question-Driven Design Process for Explainable AI User Experiences"

21 / 21 papers shown

Title
Explainable AI-Based Interface System for Weather Forecasting Model Soyeon Kim Junho Choi Yeji Choi Subeen Lee Artyom Stitsyuk Minkyoung Park Seongyeop Jeong Youhyun Baek Jaesik Choi XAI 126 2 0 01 Apr 2025
Output Scouting: Auditing Large Language Models for Catastrophic Responses Andrew Bell Joao Fonseca KELM 130 2 0 04 Oct 2024
Responsible AI Question Bank: A Comprehensive Tool for AI Risk Assessment Sung Une Lee Harsha Perera Yue Liu Boming Xia Qinghua Lu Liming Zhu Olivier Salvado Jon Whittle 113 1 0 02 Aug 2024
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty Umang Bhatt Javier Antorán Yunfeng Zhang Q. V. Liao P. Sattigeri ... L. Nachman R. Chunara Madhulika Srikumar Adrian Weller Alice Xiang 115 251 0 15 Nov 2020
Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study Ahmed Alqaraawi M. Schuessler Philipp Weiß Enrico Costanza N. Bianchi-Berthouze AAML FAtt XAI 68 200 0 03 Feb 2020
Proxy Tasks and Subjective Measures Can Be Misleading in Evaluating Explainable AI Systems Zana Buçinca Phoebe Lin Krzysztof Z. Gajos Elena L. Glassman ELM 84 288 0 22 Jan 2020
CheXplain: Enabling Physicians to Explore and UnderstandData-Driven, AI-Enabled Medical Imaging Analysis Yao Xie Melody Chen David Kao Ge Gao Xiang Ánthony' Chen 123 129 0 15 Jan 2020
"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans Vivian Lai Han Liu Chenhao Tan 84 143 0 14 Jan 2020
Questioning the AI: Informing Design Practices for Explainable AI User Experiences Q. V. Liao D. Gruen Sarah Miller 135 725 0 08 Jan 2020
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques Vijay Arya Rachel K. E. Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind ... Karthikeyan Shanmugam Moninder Singh Kush R. Varshney Dennis L. Wei Yunfeng Zhang XAI 74 393 0 06 Sep 2019
Explainability in Human-Agent Systems A. Rosenfeld A. Richardson XAI 83 206 0 17 Apr 2019
Explaining Explanations in AI Brent Mittelstadt Chris Russell Sandra Wachter XAI 116 667 0 04 Nov 2018
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias Rachel K. E. Bellamy Kuntal Dey Michael Hind Samuel C. Hoffman Stephanie Houde ... Diptikalyan Saha P. Sattigeri Moninder Singh Kush R. Varshney Yunfeng Zhang FaML SyDa 105 813 0 03 Oct 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 143 166 0 20 Jun 2018
Datasheets for Datasets Timnit Gebru Jamie Morgenstern Briana Vecchione Jennifer Wortman Vaughan Hanna M. Wallach Hal Daumé Kate Crawford 296 2,201 0 23 Mar 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 129 592 0 21 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 155 3,989 0 06 Feb 2018
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 261 4,287 0 22 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,135 0 22 May 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 422 3,824 0 28 Feb 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,092 0 16 Feb 2016