How model accuracy and explanation fidelity influence user trust

26 July 2019

Papers citing "How model accuracy and explanation fidelity influence user trust"

25 / 25 papers shown

Title
Beware of "Explanations" of AI David Martens Galit Shmueli Theodoros Evgeniou Kevin Bauer Christian Janiesch ... Claudia Perlich Wouter Verbeke Alona Zharova Patrick Zschech F. Provost 36 0 0 09 Apr 2025
Don't be Fooled: The Misinformation Effect of Explanations in Human-AI Collaboration Philipp Spitzer Joshua Holstein Katelyn Morrison Kenneth Holstein Gerhard Satzger Niklas Kühl 50 3 0 19 Sep 2024
Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle Luca Deck Astrid Schomacker Timo Speith Jakob Schöffer Lena Kästner Niklas Kühl 48 4 0 29 Apr 2024
Designing for Complementarity: A Conceptual Framework to Go Beyond the Current Paradigm of Using XAI in Healthcare Elisa Rubegni Omran Ayoub Stefania Maria Rita Rizzo Marco Barbero G. Bernegger Francesca Faraci Francesca Mangili Emiliano Soldini P. Trimboli Alessandro Facchini 34 1 0 06 Apr 2024
Influence based explainability of brain tumors segmentation in multimodal Magnetic Resonance Imaging Tommaso Torda Andrea Ciardiello Simona Gargiulo Greta Grillo Simone Scardapane Cecilia Voena S. Giagu 34 0 0 05 Apr 2024
Trust, distrust, and appropriate reliance in (X)AI: a survey of empirical evaluation of user trust Roel W. Visser Tobias M. Peters Ingrid Scharlau Barbara Hammer 29 5 0 04 Dec 2023
Predictability and Comprehensibility in Post-Hoc XAI Methods: A User-Centered Analysis Anahid N. Jalali Bernhard Haslhofer Simone Kriglstein Andreas Rauber FAtt 42 4 0 21 Sep 2023
Automatic Textual Explanations of Concept Lattices Johannes Hirth Viktoria Horn Gerd Stumme Tom Hanika LRM 18 1 0 17 Apr 2023
How Accurate Does It Feel? -- Human Perception of Different Types of Classification Mistakes A. Papenmeier Dagmar Kern Daniel Hienert Yvonne Kammerer C. Seifert 36 19 0 13 Feb 2023
The political ideology of conversational AI: Converging evidence on ChatGPT's pro-environmental, left-libertarian orientation Jochen Hartmann Jasper Schwenzow Maximilian Witte 22 203 0 05 Jan 2023
Do Not Trust a Model Because It is Confident: Uncovering and Characterizing Unknown Unknowns to Student Success Predictors in Online-Based Learning Roberta Galici Tanja Käser Gianni Fenu Mirko Marras 36 6 0 16 Dec 2022
Concept-based Explanations using Non-negative Concept Activation Vectors and Decision Tree for CNN Models Gayda Mutahar Tim Miller FAtt 29 6 0 19 Nov 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 45 78 0 06 May 2022
User Trust on an Explainable AI-based Medical Diagnosis Support System Yao Rong N. Castner Efe Bozkir Enkelejda Kasneci 26 8 0 26 Apr 2022
Diagnosing AI Explanation Methods with Folk Concepts of Behavior Alon Jacovi Jasmijn Bastings Sebastian Gehrmann Yoav Goldberg Katja Filippova 41 16 0 27 Jan 2022
Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions Eoin Delaney Derek Greene Mark T. Keane 38 24 0 20 Jul 2021
Pitfalls of Explainable ML: An Industry Perspective Sahil Verma Aditya Lahiri John P. Dickerson Su-In Lee XAI 21 9 0 14 Jun 2021
Assessing the Impact of Automated Suggestions on Decision Making: Domain Experts Mediate Model Errors but Take Less Initiative A. Levy Monica Agrawal Arvind Satyanarayan David Sontag 24 75 0 08 Mar 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
The Role of Domain Expertise in User Trust and the Impact of First Impressions with Intelligent Systems Mahsan Nourani J. King Eric D. Ragan 25 99 0 20 Aug 2020
Machine Learning Explanations to Prevent Overtrust in Fake News Detection Sina Mohseni Fan Yang Shiva K. Pentyala Mengnan Du Yi Liu Nic Lupfer Xia Hu Shuiwang Ji Eric D. Ragan 21 41 0 24 Jul 2020
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition Mahsan Nourani Chiradeep Roy Tahrima Rahman Eric D. Ragan Nicholas Ruozzi Vibhav Gogate AAML 17 17 0 05 May 2020
Deceptive AI Explanations: Creation and Detection Johannes Schneider Christian Meske Michalis Vlachos 34 28 0 21 Jan 2020
AI for Explaining Decisions in Multi-Agent Environments Sarit Kraus A. Azaria J. Fiosina Maike Greve Noam Hazon L. Kolbe Tim-Benjamin Lembcke J. P. Müller Sören Schleibaum M. Vollrath 33 40 0 10 Oct 2019
A Human-Grounded Evaluation Benchmark for Local Explanations of Machine Learning Sina Mohseni Jeremy E. Block Eric D. Ragan FAtt XAI 31 61 0 16 Jan 2018