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

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

29 December 2021
Kacper Sokol
Peter A. Flach
ArXivPDFHTML

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

6 / 6 papers shown
Title
Mind the Gap! Bridging Explainable Artificial Intelligence and Human
  Understanding with Luhmann's Functional Theory of Communication
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
What and How of Machine Learning Transparency: Building Bespoke
  Explainability Tools with Interoperable Algorithmic Components
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
23
8
0
08 Sep 2022
Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model
  Multiplicity
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
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
415
0
15 Feb 2021
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,233
0
24 Jun 2017
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
225
3,672
0
28 Feb 2017
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