Explainability Pitfalls: Beyond Dark Patterns in Explainable AI

26 September 2021

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

7 / 7 papers shown

Title
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 21 1 0 21 Oct 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 16 0 0 22 Feb 2024
The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice Fernando Delgado Stephen Yang Michael A. Madaio Qian Yang 56 98 0 02 Oct 2023
Explainability in reinforcement learning: perspective and position Agneza Krajna Mario Brčič T. Lipić Juraj Dončević 16 26 0 22 Mar 2022
Undoing Seamlessness: Exploring Seams for Critical Visualization N. Hengesbach 8 8 0 04 Mar 2022
How to Support Users in Understanding Intelligent Systems? Structuring the Discussion Malin Eiband Daniel Buschek H. Hussmann 26 24 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 286 4,143 0 23 Aug 2019