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Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to
  Stop Worrying and Love the Social and Behavioural Sciences

Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences

2 December 2017
Tim Miller
Piers Howe
L. Sonenberg
    AI4TS
    SyDa
ArXivPDFHTML

Papers citing "Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences"

10 / 10 papers shown
Title
GraphXAIN: Narratives to Explain Graph Neural Networks
GraphXAIN: Narratives to Explain Graph Neural Networks
Mateusz Cedro
David Martens
75
0
0
04 Nov 2024
A Mechanistic Explanatory Strategy for XAI
A Mechanistic Explanatory Strategy for XAI
Marcin Rabiza
78
1
0
02 Nov 2024
Opening the Black Box of Deep Neural Networks via Information
Opening the Black Box of Deep Neural Networks via Information
Ravid Shwartz-Ziv
Naftali Tishby
AI4CE
63
1,399
0
02 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
338
3,742
0
28 Feb 2017
Generating Visual Explanations
Generating Visual Explanations
Lisa Anne Hendricks
Zeynep Akata
Marcus Rohrbach
Jeff Donahue
Bernt Schiele
Trevor Darrell
VLM
FAtt
58
620
0
28 Mar 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
422
16,765
0
16 Feb 2016
Graying the black box: Understanding DQNs
Graying the black box: Understanding DQNs
Tom Zahavy
Nir Ben-Zrihem
Shie Mannor
58
263
0
08 Feb 2016
Zero-Shot Event Detection by Multimodal Distributional Semantic
  Embedding of Videos
Zero-Shot Event Detection by Multimodal Distributional Semantic Embedding of Videos
Mohamed Elhoseiny
Jingen Liu
Hui Cheng
H. Sawhney
Ahmed Elgammal
34
26
0
02 Dec 2015
Plan Explicability and Predictability for Robot Task Planning
Plan Explicability and Predictability for Robot Task Planning
Yu-an Zhang
S. Sreedharan
Anagha Kulkarni
Tathagata Chakraborti
Hankui Zhuo
S. Kambhampati
27
175
0
25 Nov 2015
Interpretable classifiers using rules and Bayesian analysis: Building a
  better stroke prediction model
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model
Benjamin Letham
Cynthia Rudin
Tyler H. McCormick
D. Madigan
FAtt
45
743
0
05 Nov 2015
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