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Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making

23 September 2022

Papers citing "Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making"

32 / 32 papers shown

Title
Perils of Label Indeterminacy: A Case Study on Prediction of Neurological Recovery After Cardiac Arrest Jakob Schoeffer Maria De-Arteaga Jonathan Elmer 402 0 0 05 Apr 2025
Personalized Help for Optimizing Low-Skilled Users' Strategy Feng Gu Wichayaporn Wongkamjan Jordan Lee Boyd-Graber Jonathan K. Kummerfeld Denis Peskoff Jonathan May 91 0 0 14 Nov 2024
Appropriate Reliance on AI Advice: Conceptualization and the Effect of Explanations Max Schemmer Niklas Kühl Carina Benz Andrea Bartos G. Satzger 50 107 0 04 Feb 2023
Charting the Sociotechnical Gap in Explainable AI: A Framework to Address the Gap in XAI Upol Ehsan Koustuv Saha M. D. Choudhury Mark O. Riedl 86 61 0 01 Feb 2023
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations Valerie Chen Q. V. Liao Jennifer Wortman Vaughan Gagan Bansal 87 109 0 18 Jan 2023
Explanations Can Reduce Overreliance on AI Systems During Decision-Making Helena Vasconcelos Matthew Jörke Madeleine Grunde-McLaughlin Tobias Gerstenberg Michael S. Bernstein Ranjay Krishna 64 172 0 13 Dec 2022
Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservables Kenneth Holstein Maria De-Arteaga Lakshmi Tumati Yanghuidi Cheng 181 24 0 28 Jul 2022
Algorithmic Fairness in Business Analytics: Directions for Research and Practice Maria De-Arteaga Stefan Feuerriegel M. Saar-Tsechansky FaML 98 42 0 22 Jul 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 59 57 0 10 May 2022
Diversity in Sociotechnical Machine Learning Systems S. Fazelpour Maria De-Arteaga 60 37 0 19 Jul 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 59 313 0 19 Feb 2021
An Analysis of LIME for Text Data Dina Mardaoui Damien Garreau FAtt 169 45 0 23 Oct 2020
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI Alon Jacovi Ana Marasović Tim Miller Yoav Goldberg 304 444 0 15 Oct 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 81 597 0 26 Jun 2020
Does Explainable Artificial Intelligence Improve Human Decision-Making? Y. Alufaisan L. Marusich J. Bakdash Yan Zhou Murat Kantarcioglu XAI 51 95 0 19 Jun 2020
Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey Arun Das P. Rad XAI 152 603 0 16 Jun 2020
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism Keri Mallari K. Quinn Paul Johns Sarah Tan Divya Ramesh Ece Kamar FaML 46 30 0 04 Feb 2020
"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans Vivian Lai Han Liu Chenhao Tan 75 141 0 14 Jan 2020
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations Himabindu Lakkaraju Osbert Bastani 59 255 0 15 Nov 2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods Dylan Slack Sophie Hilgard Emily Jia Sameer Singh Himabindu Lakkaraju FAtt AAML MLAU 75 819 0 06 Nov 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 121 6,269 0 22 Oct 2019
What does it mean to solve the problem of discrimination in hiring? Social, technical and legal perspectives from the UK on automated hiring systems Javier Sánchez-Monedero L. Dencik L. Edwards 69 136 0 28 Sep 2019
Learning to Deceive with Attention-Based Explanations Danish Pruthi Mansi Gupta Bhuwan Dhingra Graham Neubig Zachary Chase Lipton 74 193 0 17 Sep 2019
Fairwashing: the risk of rationalization Ulrich Aïvodji Hiromi Arai O. Fortineau Sébastien Gambs Satoshi Hara Alain Tapp FaML 52 147 0 28 Jan 2019
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting Maria De-Arteaga Alexey Romanov Hanna M. Wallach J. Chayes C. Borgs Alexandra Chouldechova S. Geyik K. Kenthapadi Adam Tauman Kalai 186 458 0 27 Jan 2019
On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection Vivian Lai Chenhao Tan 78 377 0 19 Nov 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 129 3,961 0 06 Feb 2018
How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation Menaka Narayanan Emily Chen Jeffrey He Been Kim S. Gershman Finale Doshi-Velez FAtt XAI 104 242 0 02 Feb 2018
Ít's Reducing a Human Being to a Percentage'; Perceptions of Justice in Algorithmic Decisions Reuben Binns Max Van Kleek Michael Veale Ulrik Lyngs Jun Zhao N. Shadbolt FaML 56 541 0 31 Jan 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 300 2,114 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 228 4,312 0 07 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,990 0 16 Feb 2016