What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components

8 September 2022

Papers citing "What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components"

3 / 3 papers shown

Title
Mind the Gap! Bridging Explainable Artificial Intelligence and Human Understanding with Luhmann's Functional Theory of Communication B. Keenan Kacper Sokol 6 7 0 07 Feb 2023
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems Kacper Sokol Alexander Hepburn Rafael Poyiadzi M. Clifford Raúl Santos-Rodríguez Peter A. Flach 27 29 0 08 Sep 2022
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence Kacper Sokol Peter A. Flach 21 20 0 29 Dec 2021