Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs

23 April 2020

Papers citing "Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs"

39 / 89 papers shown

Title
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values Zijie J. Wang Alex Kale Harsha Nori P. Stella M. Nunnally Duen Horng Chau Mihaela Vorvoreanu J. W. Vaughan R. Caruana KELM 69 27 0 30 Jun 2022
RES: A Robust Framework for Guiding Visual Explanation Yuyang Gao Tong Sun Guangji Bai Siyi Gu S. Hong Liang Zhao FAtt AAML XAI 34 32 0 27 Jun 2022
Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI Q. V. Liao Yunfeng Zhang Ronny Luss Finale Doshi-Velez Amit Dhurandhar 26 81 0 22 Jun 2022
Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations Jessica Dai Sohini Upadhyay Ulrich Aïvodji Stephen H. Bach Himabindu Lakkaraju 53 57 0 15 May 2022
Are Metrics Enough? Guidelines for Communicating and Visualizing Predictive Models to Subject Matter Experts Ashley Suh G. Appleby Erik W. Anderson Luca A. Finelli Remco Chang Dylan Cashman 38 8 0 11 May 2022
Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theory Harmanpreet Kaur Eytan Adar Eric Gilbert Cliff Lampe 16 59 0 10 May 2022
Interactive Model Cards: A Human-Centered Approach to Model Documentation Anamaria Crisan Margaret Drouhard Jesse Vig Nazneen Rajani HAI 42 87 0 05 May 2022
Artificial Concepts of Artificial Intelligence: Institutional Compliance and Resistance in AI Startups Amy A. Winecoff E. A. Watkins 35 17 0 02 Mar 2022
The Need for Interpretable Features: Motivation and Taxonomy Alexandra Zytek Ignacio Arnaldo Dongyu Liu Laure Berti-Equille K. Veeramachaneni FAtt XAI 15 13 0 23 Feb 2022
Machine Explanations and Human Understanding Chacha Chen Shi Feng Amit Sharma Chenhao Tan 35 24 0 08 Feb 2022
Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment Yuyang Gao Tong Sun Liang Zhao Sungsoo Ray Hong HAI 30 37 0 06 Feb 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 194 186 0 03 Feb 2022
GAM Changer: Editing Generalized Additive Models with Interactive Visualization Zijie J. Wang Alex Kale Harsha Nori P. Stella M. Nunnally Duen Horng Chau Mihaela Vorvoreanu Jennifer Wortman Vaughan R. Caruana KELM 19 24 0 06 Dec 2021
Learning Optimal Predictive Checklists Haoran Zhang Q. Morris Berk Ustun Marzyeh Ghassemi 26 11 0 02 Dec 2021
Hierarchical Decision Ensembles- An inferential framework for uncertain Human-AI collaboration in forensic examinations Ganesh Krishnan H. Hofmann 17 0 0 31 Oct 2021
IAC: A Framework for Enabling Patient Agency in the Use of AI-Enabled Healthcare Chinasa T. Okolo Michelle González Amador 24 0 0 29 Oct 2021
Human-Centered Explainable AI (XAI): From Algorithms to User Experiences Q. V. Liao R. Varshney 23 225 0 20 Oct 2021
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development Aspen K. Hopkins Serena Booth 29 45 0 06 Oct 2021
Explanation Strategies as an Empirical-Analytical Lens for Socio-Technical Contextualization of Machine Learning Interpretability J. Benjamin C. Kinkeldey Claudia Muller-Birn Tim Korjakow Eva-Maria Herbst 79 8 0 24 Sep 2021
AdViCE: Aggregated Visual Counterfactual Explanations for Machine Learning Model Validation Oscar Gomez Steffen Holter Jun Yuan E. Bertini AAML CML HAI 24 21 0 12 Sep 2021
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence David Alvarez-Melis Harmanpreet Kaur Hal Daumé Hanna M. Wallach Jennifer Wortman Vaughan FAtt 56 28 0 27 Apr 2021
FeatureEnVi: Visual Analytics for Feature Engineering Using Stepwise Selection and Semi-Automatic Extraction Approaches Angelos Chatzimparmpas Rafael M. Martins Kostiantyn Kucher Andreas Kerren 37 22 0 26 Mar 2021
Interpretable Machine Learning: Moving From Mythos to Diagnostics Valerie Chen Jeffrey Li Joon Sik Kim Gregory Plumb Ameet Talwalkar 32 29 0 10 Mar 2021
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs Harini Suresh Kathleen M. Lewis John Guttag Arvind Satyanarayan FAtt 45 25 0 17 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
Model-agnostic interpretation by visualization of feature perturbations Wilson E. Marcílio-Jr D. M. Eler Fabricio A. Breve AAML 11 1 0 26 Jan 2021
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs Harini Suresh Steven R. Gomez K. Nam Arvind Satyanarayan 34 126 0 24 Jan 2021
Dissonance Between Human and Machine Understanding Zijian Zhang Jaspreet Singh U. Gadiraju Avishek Anand 59 74 0 18 Jan 2021
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows Doris Xin Eva Yiwei Wu D. Lee Niloufar Salehi Aditya G. Parameswaran 62 91 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 43 394 0 12 Jan 2021
Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop Anamaria Crisan Brittany Fiore-Gartland 31 50 0 12 Jan 2021
Modeling Disclosive Transparency in NLP Application Descriptions Michael Stephen Saxon Sharon Levy Xinyi Wang Alon Albalak Jiaming Ji 27 7 0 02 Jan 2021
When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making S. McGrath Parth Mehta Alexandra Zytek Isaac Lage Himabindu Lakkaraju UD 16 25 0 12 Nov 2020
Explainable Machine Learning for Public Policy: Use Cases, Gaps, and Research Directions Kasun Amarasinghe Kit Rodolfa Hemank Lamba Rayid Ghani ELM XAI 29 51 0 27 Oct 2020
Towards Evaluating Exploratory Model Building Process with AutoML Systems Sungsoo Ray Hong Sonia Castelo Vito DÓrazio Christopher Bethune Aécio Santos Scott Langevin D. Jonker E. Bertini J. Freire HAI 17 4 0 01 Sep 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 42 584 0 26 Jun 2020
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI Dakuo Wang Justin D. Weisz Michael J. Muller Parikshit Ram Werner Geyer Casey Dugan Y. Tausczik Horst Samulowitz Alexander G. Gray 178 311 0 05 Sep 2019
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 195 742 0 13 Dec 2018
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,698 0 28 Feb 2017