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Avoiding Discrimination through Causal Reasoning
v1v2 (latest)

Avoiding Discrimination through Causal Reasoning

8 June 2017
Niki Kilbertus
Mateo Rojas-Carulla
Giambattista Parascandolo
Moritz Hardt
Dominik Janzing
Bernhard Schölkopf
    FaMLCML
ArXiv (abs)PDFHTML

Papers citing "Avoiding Discrimination through Causal Reasoning"

50 / 312 papers shown
Title
Uncovering Bias Paths with LLM-guided Causal Discovery: An Active Learning and Dynamic Scoring Approach
Uncovering Bias Paths with LLM-guided Causal Discovery: An Active Learning and Dynamic Scoring Approach
Khadija Zanna
Akane Sano
15
0
0
13 Jun 2025
DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation
DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation
Emre Kavak
Tom Nuno Wolf
Christian Wachinger
CML
20
0
0
13 Jun 2025
Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants
Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants
D. Tramontano
Yaroslav Kivva
Saber Salehkaleybar
Mathias Drton
Negar Kiyavash
CML
110
0
0
05 Jun 2025
Mitigating Context Bias in Domain Adaptation for Object Detection using Mask Pooling
Mitigating Context Bias in Domain Adaptation for Object Detection using Mask Pooling
Hojun Son
Asma Almutairi
Arpan Kusari
127
0
0
24 May 2025
Am I Being Treated Fairly? A Conceptual Framework for Individuals to Ascertain Fairness
Am I Being Treated Fairly? A Conceptual Framework for Individuals to Ascertain Fairness
Juliett Suárez Ferreira
Marija Slavkovik
Jorge Casillas
FaML
135
0
0
03 Apr 2025
Causal Feature Learning in the Social Sciences
Causal Feature Learning in the Social Sciences
Jingzhou Huang
Jiuyao Lu
Alexander Williams Tolbert
CML
84
0
0
17 Mar 2025
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Ruta Binkyte
Ivaxi Sheth
Zhijing Jin
Mohammad Havaei
Bernhard Schölkopf
Mario Fritz
556
1
0
28 Feb 2025
Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses
Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses
Sourbh Bhadane
Joris Mooij
Philip A. Boeken
O. Zoeter
155
0
0
17 Feb 2025
Fairness Amidst Non-IID Graph Data: A Literature Review
Fairness Amidst Non-IID Graph Data: A Literature Review
Wenbin Zhang
Shimei Pan
Shuigeng Zhou
T. Walsh
FaMLOOD
105
12
0
28 Jan 2025
Lookahead Counterfactual Fairness
Lookahead Counterfactual Fairness
Zhiqun Zuo
Tian Xie
Xuwei Tan
Xueru Zhang
Mohammad Mahdi Khalili
FaML
172
0
0
02 Dec 2024
Debiasing Alternative Data for Credit Underwriting Using Causal
  Inference
Debiasing Alternative Data for Credit Underwriting Using Causal Inference
Chris Lam
CML
44
0
0
29 Oct 2024
Considerations for Distribution Shift Robustness of Diagnostic Models in
  Healthcare
Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare
Arno Blaas
Adam Goliñski
Andrew C. Miller
Luca Zappella
J. Jacobsen
Christina Heinze-Deml
OOD
74
0
0
25 Oct 2024
Using Protected Attributes to Consider Fairness in Multi-Agent Systems
Using Protected Attributes to Consider Fairness in Multi-Agent Systems
Gabriele La Malfa
Jie M. Zhang
Michael Luck
Elizabeth Black
FaML
45
0
0
16 Oct 2024
DiffusionCounterfactuals: Inferring High-dimensional Counterfactuals
  with Guidance of Causal Representations
DiffusionCounterfactuals: Inferring High-dimensional Counterfactuals with Guidance of Causal Representations
Jiageng Zhu
Hanchen Xie
Jiazhi Li
Wael Abd-Almageed
DiffM
89
1
0
30 Jul 2024
Formalising Anti-Discrimination Law in Automated Decision Systems
Formalising Anti-Discrimination Law in Automated Decision Systems
Holli Sargeant
Måns Magnusson
FaML
106
0
0
29 Jun 2024
Dancing in the Shadows: Harnessing Ambiguity for Fairer Classifiers
Dancing in the Shadows: Harnessing Ambiguity for Fairer Classifiers
Ainhize Barrainkua
Paula Gordaliza
Jose A. Lozano
Novi Quadrianto
70
0
0
27 Jun 2024
Causal Inference with Latent Variables: Recent Advances and Future
  Prospectives
Causal Inference with Latent Variables: Recent Advances and Future Prospectives
Yaochen Zhu
Yinhan He
Jing Ma
Mengxuan Hu
Sheng Li
Jundong Li
CML
73
3
0
20 Jun 2024
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
124
4
0
10 Jun 2024
Causal Effect Identification in LiNGAM Models with Latent Confounders
Causal Effect Identification in LiNGAM Models with Latent Confounders
D. Tramontano
Yaroslav Kivva
Saber Salehkaleybar
Mathias Drton
Negar Kiyavash
CML
93
3
0
04 Jun 2024
Fairness-Accuracy Trade-Offs: A Causal Perspective
Fairness-Accuracy Trade-Offs: A Causal Perspective
Drago Plečko
Elias Bareinboim
72
3
0
24 May 2024
Local Causal Discovery for Structural Evidence of Direct Discrimination
Local Causal Discovery for Structural Evidence of Direct Discrimination
Jacqueline R. M. A. Maasch
Kyra Gan
Violet Chen
Agni Orfanoudaki
Nil-Jana Akpinar
Fei Wang
68
2
0
23 May 2024
Challenging the Human-in-the-loop in Algorithmic Decision-making
Challenging the Human-in-the-loop in Algorithmic Decision-making
Sebastian Tschiatschek
Eugenia Stamboliev
Timothée Schmude
Mark Coeckelbergh
Laura M. Koesten
87
1
0
17 May 2024
Intrinsic Fairness-Accuracy Tradeoffs under Equalized Odds
Intrinsic Fairness-Accuracy Tradeoffs under Equalized Odds
Meiyu Zhong
Ravi Tandon
FaML
76
4
0
12 May 2024
Utility-Fairness Trade-Offs and How to Find Them
Utility-Fairness Trade-Offs and How to Find Them
Sepehr Dehdashtian
Bashir Sadeghi
Vishnu Boddeti
80
6
0
15 Apr 2024
Auditing the Use of Language Models to Guide Hiring Decisions
Auditing the Use of Language Models to Guide Hiring Decisions
Johann D. Gaebler
Sharad Goel
Aziz Huq
Prasanna Tambe
MLAU
89
12
0
03 Apr 2024
Addressing Both Statistical and Causal Gender Fairness in NLP Models
Addressing Both Statistical and Causal Gender Fairness in NLP Models
Hannah Chen
Yangfeng Ji
David Evans
77
4
0
30 Mar 2024
The Pursuit of Fairness in Artificial Intelligence Models: A Survey
The Pursuit of Fairness in Artificial Intelligence Models: A Survey
Tahsin Alamgir Kheya
Mohamed Reda Bouadjenek
Sunil Aryal
82
9
0
26 Mar 2024
Fair Multivariate Adaptive Regression Splines for Ensuring Equity and
  Transparency
Fair Multivariate Adaptive Regression Splines for Ensuring Equity and Transparency
Parian Haghighat
Denisa Gándara
Lulu Kang
Hadis Anahideh
59
0
0
23 Feb 2024
A Causal Framework to Evaluate Racial Bias in Law Enforcement Systems
A Causal Framework to Evaluate Racial Bias in Law Enforcement Systems
Jessy Xinyi Han
Andrew Miller
S. C. Watkins
Christopher Winship
Fotini Christia
Devavrat Shah
35
1
0
22 Feb 2024
Connecting Algorithmic Fairness to Quality Dimensions in Machine
  Learning in Official Statistics and Survey Production
Connecting Algorithmic Fairness to Quality Dimensions in Machine Learning in Official Statistics and Survey Production
Patrick Oliver Schenk
Christoph Kern
FaML
96
0
0
14 Feb 2024
Causal Feature Selection for Responsible Machine Learning
Causal Feature Selection for Responsible Machine Learning
Raha Moraffah
Paras Sheth
Saketh Vishnubhatla
Huan Liu
CML
60
2
0
05 Feb 2024
A New Paradigm for Counterfactual Reasoning in Fairness and Recourse
A New Paradigm for Counterfactual Reasoning in Fairness and Recourse
Lucius E.J. Bynum
Joshua R. Loftus
Julia Stoyanovich
64
4
0
25 Jan 2024
Interventional Fairness on Partially Known Causal Graphs: A Constrained
  Optimization Approach
Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach
Aoqi Zuo
Yiqing Li
Susan Wei
Biwei Huang
FaML
72
6
0
19 Jan 2024
SoK: Taming the Triangle -- On the Interplays between Fairness,
  Interpretability and Privacy in Machine Learning
SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning
Julien Ferry
Ulrich Aïvodji
Sébastien Gambs
Marie-José Huguet
Mohamed Siala
FaML
69
5
0
22 Dec 2023
GroupMixNorm Layer for Learning Fair Models
GroupMixNorm Layer for Learning Fair Models
Anubha Pandey
Aditi Rai
Maneet Singh
Deepak L. Bhatt
Tanmoy Bhowmik
51
0
0
19 Dec 2023
Evaluating and Mitigating Discrimination in Language Model Decisions
Evaluating and Mitigating Discrimination in Language Model Decisions
Alex Tamkin
Amanda Askell
Liane Lovitt
Esin Durmus
Nicholas Joseph
Shauna Kravec
Karina Nguyen
Jared Kaplan
Deep Ganguli
95
76
0
06 Dec 2023
Causal Fairness under Unobserved Confounding: A Neural Sensitivity
  Framework
Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
Maresa Schröder
Dennis Frauen
Stefan Feuerriegel
CML
71
6
0
30 Nov 2023
Enhancing the Performance of Neural Networks Through Causal Discovery
  and Integration of Domain Knowledge
Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge
Xiaoge Zhang
Xiao-Lin Wang
Fenglei Fan
Yiu-ming Cheung
Indranil Bose
90
1
0
29 Nov 2023
Challenges of Large Language Models for Mental Health Counseling
Challenges of Large Language Models for Mental Health Counseling
N. C. Chung
George C. Dyer
L. Brocki
LM&MAAI4MH
123
16
0
23 Nov 2023
Procedural Fairness Through Decoupling Objectionable Data Generating
  Components
Procedural Fairness Through Decoupling Objectionable Data Generating Components
Zeyu Tang
Jialu Wang
Yang Liu
Peter Spirtes
Kun Zhang
50
2
0
05 Nov 2023
Causal Fair Metric: Bridging Causality, Individual Fairness, and
  Adversarial Robustness
Causal Fair Metric: Bridging Causality, Individual Fairness, and Adversarial Robustness
A. Ehyaei
G. Farnadi
Samira Samadi
98
1
0
30 Oct 2023
Causality-Inspired Fair Representation Learning for Multimodal Recommendation
Weixin Chen
Li Chen
Yongxin Ni
Yuhan Zhao
40
2
0
26 Oct 2023
The Impact of Explanations on Fairness in Human-AI Decision-Making:
  Protected vs Proxy Features
The Impact of Explanations on Fairness in Human-AI Decision-Making: Protected vs Proxy Features
Navita Goyal
Connor Baumler
Tin Trung Nguyen
Hal Daumé
78
8
0
12 Oct 2023
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda
  for Developing Practical Guidelines and Tools
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools
Maximilian Schambach
Rakshit Naidu
Rayid Ghani
Kit T. Rodolfa
Daniel E. Ho
Hoda Heidari
FaML
89
17
0
29 Sep 2023
Measuring, Interpreting, and Improving Fairness of Algorithms using
  Causal Inference and Randomized Experiments
Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments
James Enouen
Tianshu Sun
Yan Liu
FaML
60
0
0
04 Sep 2023
Adaptation Speed Analysis for Fairness-aware Causal Models
Adaptation Speed Analysis for Fairness-aware Causal Models
Yujie Lin
Chen Zhao
Minglai Shao
Xujiang Zhao
Haifeng Chen
40
5
0
31 Aug 2023
Fair Models in Credit: Intersectional Discrimination and the
  Amplification of Inequity
Fair Models in Credit: Intersectional Discrimination and the Amplification of Inequity
S. Kim
Stefan Lessmann
G. Andreeva
Michael Rovatsos
FaML
66
5
0
01 Aug 2023
Learning Fair Classifiers via Min-Max F-divergence Regularization
Learning Fair Classifiers via Min-Max F-divergence Regularization
Meiyu Zhong
Ravi Tandon
FaML
43
4
0
28 Jun 2023
Fairness Aware Counterfactuals for Subgroups
Fairness Aware Counterfactuals for Subgroups
Loukas Kavouras
Konstantinos Tsopelas
G. Giannopoulos
Dimitris Sacharidis
Eleni Psaroudaki
Nikolaos Theologitis
D. Rontogiannis
Dimitris Fotakis
Ioannis Emiris
96
8
0
26 Jun 2023
Insights From Insurance for Fair Machine Learning
Insights From Insurance for Fair Machine Learning
Christiane Fröhlich
Robert C. Williamson
FaML
70
8
0
26 Jun 2023
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