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Logics and practices of transparency and opacity in real-world
  applications of public sector machine learning
v1v2v3 (latest)

Logics and practices of transparency and opacity in real-world applications of public sector machine learning

19 June 2017
Michael Veale
ArXiv (abs)PDFHTML

Papers citing "Logics and practices of transparency and opacity in real-world applications of public sector machine learning"

3 / 3 papers shown
Title
Trust in Data Science: Collaboration, Translation, and Accountability in
  Corporate Data Science Projects
Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects
Samir Passi
S. Jackson
231
113
0
09 Feb 2020
ABOUT ML: Annotation and Benchmarking on Understanding and Transparency
  of Machine Learning Lifecycles
ABOUT ML: Annotation and Benchmarking on Understanding and Transparency of Machine Learning Lifecycles
Inioluwa Deborah Raji
Jingyi Yang
92
38
0
12 Dec 2019
The Bouncer Problem: Challenges to Remote Explainability
The Bouncer Problem: Challenges to Remote Explainability
Erwan Le Merrer
Gilles Tredan
57
8
0
03 Oct 2019
1