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A Causal Bayesian Networks Viewpoint on Fairness

A Causal Bayesian Networks Viewpoint on Fairness

15 July 2019
Silvia Chiappa
William S. Isaac
    FaML
ArXivPDFHTML

Papers citing "A Causal Bayesian Networks Viewpoint on Fairness"

31 / 31 papers shown
Title
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing
Jitao Wang
C. Shi
John D. Piette
Joshua R. Loftus
Donglin Zeng
Zhenke Wu
OffRL
61
0
0
10 Jan 2025
Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges
Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges
Usman Gohar
Zeyu Tang
Jialu Wang
Kun Zhang
Peter Spirtes
Yang Liu
Lu Cheng
FaML
60
3
0
10 Jun 2024
A Review of the Role of Causality in Developing Trustworthy AI Systems
A Review of the Role of Causality in Developing Trustworthy AI Systems
Niloy Ganguly
Dren Fazlija
Maryam Badar
M. Fisichella
Sandipan Sikdar
...
Koustav Rudra
Manolis Koubarakis
Gourab K. Patro
W. Z. E. Amri
Wolfgang Nejdl
CML
39
23
0
14 Feb 2023
D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling
  Algorithmic Bias
D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Bias
Bhavya Ghai
Klaus Mueller
17
40
0
10 Aug 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey
Max Hort
Zhenpeng Chen
Jie M. Zhang
Mark Harman
Federica Sarro
FaML
AI4CE
31
159
0
14 Jul 2022
What-is and How-to for Fairness in Machine Learning: A Survey,
  Reflection, and Perspective
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective
Zeyu Tang
Jiji Zhang
Kun Zhang
FaML
25
26
0
08 Jun 2022
Fairness in Recommendation: Foundations, Methods and Applications
Fairness in Recommendation: Foundations, Methods and Applications
Yunqi Li
H. Chen
Shuyuan Xu
Yingqiang Ge
Juntao Tan
Shuchang Liu
Yongfeng Zhang
FaML
OffRL
100
41
0
26 May 2022
What Is Fairness? On the Role of Protected Attributes and Fictitious
  Worlds
What Is Fairness? On the Role of Protected Attributes and Fictitious Worlds
Ludwig Bothmann
Kristina Peters
Bernd Bischl
17
5
0
19 May 2022
Towards Intersectionality in Machine Learning: Including More
  Identities, Handling Underrepresentation, and Performing Evaluation
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
Angelina Wang
V. V. Ramaswamy
Olga Russakovsky
FaML
23
92
0
10 May 2022
The Long Arc of Fairness: Formalisations and Ethical Discourse
The Long Arc of Fairness: Formalisations and Ethical Discourse
Pola Schwöbel
Peter Remmers
16
18
0
08 Mar 2022
Selection, Ignorability and Challenges With Causal Fairness
Selection, Ignorability and Challenges With Causal Fairness
Jake Fawkes
R. Evans
Dino Sejdinovic
86
19
0
28 Feb 2022
Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for
  Introduced Unfairness
Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness
Carolyn Ashurst
Ryan Carey
Silvia Chiappa
Tom Everitt
FaML
31
15
0
22 Feb 2022
Bias and unfairness in machine learning models: a systematic literature
  review
Bias and unfairness in machine learning models: a systematic literature review
T. P. Pagano
R. B. Loureiro
F. V. N. Lisboa
G. O. R. Cruz
R. M. Peixoto
...
Maira M. Araujo
Marco A. S. Cruz
Ewerton L. S. Oliveira
Ingrid Winkler
E. G. S. Nascimento
FaML
22
21
0
16 Feb 2022
A Causal Approach for Unfair Edge Prioritization and Discrimination
  Removal
A Causal Approach for Unfair Edge Prioritization and Discrimination Removal
Pavan Ravishankar
Pranshu Malviya
Balaraman Ravindran
14
1
0
29 Nov 2021
Learning to be Fair: A Consequentialist Approach to Equitable
  Decision-Making
Learning to be Fair: A Consequentialist Approach to Equitable Decision-Making
Alex Chohlas-Wood
Madison Coots
Henry Zhu
Emma Brunskill
Sharad Goel
FaML
16
23
0
18 Sep 2021
Fairness in Machine Learning
Fairness in Machine Learning
L. Oneto
Silvia Chiappa
FaML
240
488
0
31 Dec 2020
Survey on Causal-based Machine Learning Fairness Notions
Survey on Causal-based Machine Learning Fairness Notions
K. Makhlouf
Sami Zhioua
C. Palamidessi
FaML
12
84
0
19 Oct 2020
Fairness in Machine Learning: A Survey
Fairness in Machine Learning: A Survey
Simon Caton
C. Haas
FaML
16
614
0
04 Oct 2020
A Causal Linear Model to Quantify Edge Flow and Edge Unfairness for
  UnfairEdge Prioritization and Discrimination Removal
A Causal Linear Model to Quantify Edge Flow and Edge Unfairness for UnfairEdge Prioritization and Discrimination Removal
Pavan Ravishankar
Pranshu Malviya
Balaraman Ravindran
14
1
0
10 Jul 2020
Decolonial AI: Decolonial Theory as Sociotechnical Foresight in
  Artificial Intelligence
Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence
Shakir Mohamed
Marie-Therese Png
William S. Isaac
25
394
0
08 Jul 2020
Extending the Machine Learning Abstraction Boundary: A Complex Systems
  Approach to Incorporate Societal Context
Extending the Machine Learning Abstraction Boundary: A Complex Systems Approach to Incorporate Societal Context
Donald Martin
Vinodkumar Prabhakaran
Jill A. Kuhlberg
A. Smart
William S. Isaac
FaML
6
40
0
17 Jun 2020
Causal Feature Selection for Algorithmic Fairness
Causal Feature Selection for Algorithmic Fairness
Sainyam Galhotra
Karthikeyan Shanmugam
P. Sattigeri
Kush R. Varshney
FaML
20
39
0
10 Jun 2020
Fair Bayesian Optimization
Fair Bayesian Optimization
Valerio Perrone
Michele Donini
Muhammad Bilal Zafar
Robin Schmucker
K. Kenthapadi
Cédric Archambeau
FaML
11
83
0
09 Jun 2020
Participatory Problem Formulation for Fairer Machine Learning Through
  Community Based System Dynamics
Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics
Donald Martin
Vinodkumar Prabhakaran
Jill A. Kuhlberg
A. Smart
William S. Isaac
FaML
8
62
0
15 May 2020
Causal datasheet: An approximate guide to practically assess Bayesian
  networks in the real world
Causal datasheet: An approximate guide to practically assess Bayesian networks in the real world
B. Butcher
V. Huang
Jeremy Reffin
S. Sgaier
Grace Charles
Novi Quadrianto
CML
30
17
0
12 Mar 2020
The Incentives that Shape Behaviour
The Incentives that Shape Behaviour
Ryan Carey
Eric D. Langlois
Tom Everitt
Shane Legg
CML
17
13
0
20 Jan 2020
Causality matters in medical imaging
Causality matters in medical imaging
Daniel Coelho De Castro
Ian Walker
Ben Glocker
CML
15
337
0
17 Dec 2019
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation
Reducing Sentiment Bias in Language Models via Counterfactual Evaluation
Po-Sen Huang
Huan Zhang
Ray Jiang
Robert Stanforth
Johannes Welbl
Jack W. Rae
Vishal Maini
Dani Yogatama
Pushmeet Kohli
17
206
0
08 Nov 2019
Asymmetric Shapley values: incorporating causal knowledge into
  model-agnostic explainability
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Christopher Frye
C. Rowat
Ilya Feige
16
179
0
14 Oct 2019
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
314
4,203
0
23 Aug 2019
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
204
2,082
0
24 Oct 2016
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