Explaining Explanations to Society

Explaining Explanations to Society

19 January 2019

Leilani H. Gilpin

Cecilia Testart

Nathaniel Fruchter

Papers citing "Explaining Explanations to Society"

9 / 9 papers shown

Title
Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle Luca Deck Astrid Schomacker Timo Speith Jakob Schöffer Lena Kästner Niklas Kühl 41 4 0 29 Apr 2024
Appropriate Reliance on AI Advice: Conceptualization and the Effect of Explanations Max Schemmer Niklas Kühl Carina Benz Andrea Bartos G. Satzger 19 97 0 04 Feb 2023
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 23 137 0 17 May 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques Mark T. Keane Eoin M. Kenny Eoin Delaney Barry Smyth CML 13 146 0 26 Feb 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 56 415 0 15 Feb 2021
Explainable AI for Interpretable Credit Scoring Lara Marie Demajo Vince Vella A. Dingli 35 35 0 03 Dec 2020
Play MNIST For Me! User Studies on the Effects of Post-Hoc, Example-Based Explanations & Error Rates on Debugging a Deep Learning, Black-Box Classifier Courtney Ford Eoin M. Kenny Mark T. Keane 17 6 0 10 Sep 2020
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group) Zied Bouraoui Antoine Cornuéjols Thierry Denoeux Sebastien Destercke Didier Dubois ... Jérôme Mengin H. Prade Steven Schockaert M. Serrurier Christel Vrain 18 13 0 13 Dec 2019
The Twin-System Approach as One Generic Solution for XAI: An Overview of ANN-CBR Twins for Explaining Deep Learning Mark T. Keane Eoin M. Kenny 10 13 0 20 May 2019