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Are fairness metric scores enough to assess discrimination biases in
  machine learning?

Are fairness metric scores enough to assess discrimination biases in machine learning?

8 June 2023
Fanny Jourdan
Laurent Risser
Jean-Michel Loubes
Nicholas M. Asher
    FaML
ArXivPDFHTML

Papers citing "Are fairness metric scores enough to assess discrimination biases in machine learning?"

7 / 7 papers shown
Title
On Explaining with Attention Matrices
On Explaining with Attention Matrices
Omar Naim
Nicholas Asher
36
1
0
24 Oct 2024
Evaluating Model Bias Requires Characterizing its Mistakes
Evaluating Model Bias Requires Characterizing its Mistakes
Isabela Albuquerque
Jessica Schrouff
David Warde-Farley
Ali Taylan Cemgil
Sven Gowal
Olivia Wiles
56
2
0
15 Jul 2024
A Note on Bias to Complete
A Note on Bias to Complete
Jia Xu
Mona Diab
59
2
0
18 Feb 2024
On Bias and Fairness in NLP: Investigating the Impact of Bias and
  Debiasing in Language Models on the Fairness of Toxicity Detection
On Bias and Fairness in NLP: Investigating the Impact of Bias and Debiasing in Language Models on the Fairness of Toxicity Detection
Fatma Elsafoury
Stamos Katsigiannis
38
1
0
22 May 2023
Fairness in Machine Learning
Fairness in Machine Learning
L. Oneto
Silvia Chiappa
FaML
256
492
0
31 Dec 2020
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data
  and Bayesian Inference
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference
Disi Ji
Padhraic Smyth
M. Steyvers
39
45
0
19 Oct 2020
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
207
2,092
0
24 Oct 2016
1