Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence

29 December 2021

Papers citing "Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence"

5 / 5 papers shown

Title
What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components Kacper Sokol Alexander Hepburn Raúl Santos-Rodríguez Peter A. Flach 21 8 0 08 Sep 2022
Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity Kacper Sokol Meelis Kull J. Chan Flora D. Salim 8 6 0 14 Mar 2022
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 43 411 0 15 Feb 2021
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,231 0 24 Jun 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,658 0 28 Feb 2017