Explainability Pitfalls: Beyond Dark Patterns in Explainable AI

26 September 2021

Papers citing "Explainability Pitfalls: Beyond Dark Patterns in Explainable AI"

30 / 30 papers shown

Title
Representation Engineering for Large-Language Models: Survey and Research Challenges Lukasz Bartoszcze Sarthak Munshi Bryan Sukidi Jennifer Yen Zejia Yang David Williams-King Linh Le Kosi Asuzu Carsten Maple 102 0 0 24 Feb 2025
User-centric evaluation of explainability of AI with and for humans: a comprehensive empirical study Szymon Bobek Paloma Korycińska Monika Krakowska Maciej Mozolewski Dorota Rak Magdalena Zych Magdalena Wójcik Grzegorz J. Nalepa ELM 29 1 0 21 Oct 2024
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 35 3 0 19 Sep 2024
Beyond Following: Mixing Active Initiative into Computational Creativity Zhiyu Lin Upol Ehsan Rohan Agarwal Samihan Dani Vidushi Vashishth Mark O. Riedl 41 0 0 06 Sep 2024
LLM-Generated Black-box Explanations Can Be Adversarially Helpful R. Ajwani Shashidhar Reddy Javaji Frank Rudzicz Zining Zhu AAML 37 6 0 10 May 2024
Unraveling the Dilemma of AI Errors: Exploring the Effectiveness of Human and Machine Explanations for Large Language Models Marvin Pafla Kate Larson Mark Hancock 35 6 0 11 Apr 2024
The European Commitment to Human-Centered Technology: The Integral Role of HCI in the EU AI Act's Success André Calero Valdez Moreen Heine Thomas Franke Nicole Jochems Hans-Christian Jetter Tim Schrills 21 0 0 22 Feb 2024
Beyond Behaviorist Representational Harms: A Plan for Measurement and Mitigation Jennifer Chien David Danks 34 13 0 25 Jan 2024
Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space Param S. Rajpura H. Cecotti Y. Meena 21 6 0 20 Dec 2023
Local Universal Explainer (LUX) -- a rule-based explainer with factual, counterfactual and visual explanations Szymon Bobek Grzegorz J. Nalepa 13 0 0 23 Oct 2023
An Ontology of Co-Creative AI Systems Zhiyu Lin Mark O. Riedl 16 3 0 11 Oct 2023
The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice Fernando Delgado Stephen Yang Michael A. Madaio Qian Yang 73 100 0 02 Oct 2023
How Do Analysts Understand and Verify AI-Assisted Data Analyses? Ken Gu Ruoxi Shang Tim Althoff Chenglong Wang Steven Drucker AAML 38 25 0 19 Sep 2023
The Case Against Explainability Hofit Wasserman Rozen N. Elkin-Koren Ran Gilad-Bachrach AILaw ELM 21 1 0 20 May 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 18 57 0 01 Feb 2023
Selective Explanations: Leveraging Human Input to Align Explainable AI Vivian Lai Yiming Zhang Chacha Chen Q. V. Liao Chenhao Tan 18 43 0 23 Jan 2023
Seamful XAI: Operationalizing Seamful Design in Explainable AI Upol Ehsan Q. V. Liao Samir Passi Mark O. Riedl Hal Daumé 22 20 0 12 Nov 2022
Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making Jakob Schoeffer Maria De-Arteaga Niklas Kuehl FaML 43 46 0 23 Sep 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 21 81 0 22 Jun 2022
"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Making Jakob Schoeffer Niklas Kuehl Yvette Machowski FaML 16 52 0 11 May 2022
The Conflict Between Explainable and Accountable Decision-Making Algorithms Gabriel Lima Nina Grgić-Hlavca Jin Keun Jeong M. Cha 11 37 0 11 May 2022
Interactive Model Cards: A Human-Centered Approach to Model Documentation Anamaria Crisan Margaret Drouhard Jesse Vig Nazneen Rajani HAI 25 87 0 05 May 2022
A Human-Centric Perspective on Fairness and Transparency in Algorithmic Decision-Making Jakob Schoeffer FaML 20 3 0 29 Apr 2022
On the Relationship Between Explanations, Fairness Perceptions, and Decisions Jakob Schoeffer Maria De-Arteaga Niklas Kuehl FaML 19 6 0 27 Apr 2022
Explainability in reinforcement learning: perspective and position Agneza Krajna Mario Brčič T. Lipić Juraj Dončević 28 27 0 22 Mar 2022
Undoing Seamlessness: Exploring Seams for Critical Visualization N. Hengesbach 22 8 0 04 Mar 2022
Investigating Explainability of Generative AI for Code through Scenario-based Design Jiao Sun Q. V. Liao Michael J. Muller Mayank Agarwal Stephanie Houde Kartik Talamadupula Justin D. Weisz 33 157 0 10 Feb 2022
The Who in XAI: How AI Background Shapes Perceptions of AI Explanations Upol Ehsan Samir Passi Q. V. Liao Larry Chan I-Hsiang Lee Michael J. Muller Mark O. Riedl 29 85 0 28 Jul 2021
How to Support Users in Understanding Intelligent Systems? Structuring the Discussion Malin Eiband Daniel Buschek H. Hussmann 39 28 0 22 Jan 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,203 0 23 Aug 2019