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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

24 October 2016
Alexandra Chouldechova
    FaML
ArXiv (abs)PDFHTML

Papers citing "Fair prediction with disparate impact: A study of bias in recidivism prediction instruments"

50 / 858 papers shown
Title
Equal Opportunity of Coverage in Fair Regression
Equal Opportunity of Coverage in Fair Regression
Fangxin Wang
Lu Cheng
Ruocheng Guo
Kay Liu
Philip S. Yu
216
16
0
03 Nov 2023
Causal Context Connects Counterfactual Fairness to Robust Prediction and
  Group Fairness
Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness
Jacy Reese Anthis
Victor Veitch
77
16
0
30 Oct 2023
WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit
  Courts
WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts
Elliott Ash
Naman Goel
Nianyun Li
Claudia Marangon
Peiyao Sun
162
2
0
28 Oct 2023
fairret: a Framework for Differentiable Fairness Regularization Terms
fairret: a Framework for Differentiable Fairness Regularization Terms
Maarten Buyl
Marybeth Defrance
T. D. Bie
FedML
71
4
0
26 Oct 2023
A Canonical Data Transformation for Achieving Inter- and Within-group
  Fairness
A Canonical Data Transformation for Achieving Inter- and Within-group Fairness
Zachary McBride Lazri
Ivan Brugere
Xin Tian
Dana Dachman-Soled
Antigoni Polychroniadou
Danial Dervovic
Min Wu
53
1
0
23 Oct 2023
Detection and Evaluation of bias-inducing Features in Machine learning
Detection and Evaluation of bias-inducing Features in Machine learning
Moses Openja
Gabriel Laberge
Foutse Khomh
CML
16
3
0
19 Oct 2023
Group-blind optimal transport to group parity and its constrained
  variants
Group-blind optimal transport to group parity and its constrained variants
Quan-Gen Zhou
Georgios Korpas
65
3
0
17 Oct 2023
Understanding Fairness Surrogate Functions in Algorithmic Fairness
Understanding Fairness Surrogate Functions in Algorithmic Fairness
Wei Yao
Zhanke Zhou
Zhicong Li
Bo Han
Yong Liu
77
5
0
17 Oct 2023
A Critical Survey on Fairness Benefits of Explainable AI
A Critical Survey on Fairness Benefits of Explainable AI
Luca Deck
Jakob Schoeffer
Maria De-Arteaga
Niklas Kühl
115
13
0
15 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
Post-hoc Bias Scoring Is Optimal For Fair Classification
Post-hoc Bias Scoring Is Optimal For Fair Classification
Wenlong Chen
Yegor Klochkov
Yang Liu
FaML
91
8
0
09 Oct 2023
On Prediction-Modelers and Decision-Makers: Why Fairness Requires More
  Than a Fair Prediction Model
On Prediction-Modelers and Decision-Makers: Why Fairness Requires More Than a Fair Prediction Model
Teresa Scantamburlo
Joachim Baumann
Christoph Heitz
FaML
65
6
0
09 Oct 2023
Interventions Against Machine-Assisted Statistical Discrimination
Interventions Against Machine-Assisted Statistical Discrimination
John Y. Zhu
68
0
0
06 Oct 2023
Fair Feature Selection: A Comparison of Multi-Objective Genetic
  Algorithms
Fair Feature Selection: A Comparison of Multi-Objective Genetic Algorithms
James Brookhouse
Alex Freitas
FaML
48
2
0
04 Oct 2023
Estimating and Implementing Conventional Fairness Metrics With
  Probabilistic Protected Features
Estimating and Implementing Conventional Fairness Metrics With Probabilistic Protected Features
Hadi Elzayn
Emily Black
Patrick Vossler
Nathanael Jo
Jacob Goldin
Daniel E. Ho
45
5
0
02 Oct 2023
Towards Last-layer Retraining for Group Robustness with Fewer
  Annotations
Towards Last-layer Retraining for Group Robustness with Fewer Annotations
Tyler LaBonte
Vidya Muthukumar
Abhishek Kumar
104
42
0
15 Sep 2023
Boosting Fair Classifier Generalization through Adaptive Priority
  Reweighing
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing
Zhihao Hu
Yiran Xu
Mengnan Du
Jindong Gu
Xinmei Tian
Fengxiang He
87
1
0
15 Sep 2023
Verifiable Fairness: Privacy-preserving Computation of Fairness for
  Machine Learning Systems
Verifiable Fairness: Privacy-preserving Computation of Fairness for Machine Learning Systems
Ehsan Toreini
M. Mehrnezhad
Aad van Moorsel
60
5
0
12 Sep 2023
Re-formalization of Individual Fairness
Re-formalization of Individual Fairness
Toshihiro Kamishima
FaML
25
0
0
11 Sep 2023
Developing A Fair Individualized Polysocial Risk Score (iPsRS) for
  Identifying Increased Social Risk of Hospitalizations in Patients with Type 2
  Diabetes (T2D)
Developing A Fair Individualized Polysocial Risk Score (iPsRS) for Identifying Increased Social Risk of Hospitalizations in Patients with Type 2 Diabetes (T2D)
Yu Huang
Jingchuan Guo
W. Donahoo
Zhengkang Fan
Ying Lu
Wei-Han Chen
Huilin Tang
Lori Bilello
E. Shenkman
Jiang Bian
79
1
0
05 Sep 2023
Fairness in Ranking under Disparate Uncertainty
Fairness in Ranking under Disparate Uncertainty
Richa Rastogi
Thorsten Joachims
89
3
0
04 Sep 2023
Bias and Fairness in Large Language Models: A Survey
Bias and Fairness in Large Language Models: A Survey
Isabel O. Gallegos
Ryan Rossi
Joe Barrow
Md Mehrab Tanjim
Sungchul Kim
Franck Dernoncourt
Tong Yu
Ruiyi Zhang
Nesreen Ahmed
AILaw
140
606
0
02 Sep 2023
Advancing Personalized Federated Learning: Group Privacy, Fairness, and
  Beyond
Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond
Filippo Galli
Kangsoo Jung
Sayan Biswas
C. Palamidessi
Tommaso Cucinotta
FedML
61
11
0
01 Sep 2023
Evaluating the Vulnerabilities in ML systems in terms of adversarial
  attacks
Evaluating the Vulnerabilities in ML systems in terms of adversarial attacks
John Harshith
Mantej Singh Gill
Madhan Jothimani
AAML
48
1
0
24 Aug 2023
Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks
  for Node Classification
Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node Classification
Arpit Merchant
Carlos Castillo
57
4
0
18 Aug 2023
Software Doping Analysis for Human Oversight
Software Doping Analysis for Human Oversight
Sebastian Biewer
Kevin Baum
Sarah Sterz
Holger Hermanns
Sven Hetmank
Markus Langer
Anne Lauber-Rönsberg
Franz Lehr
63
4
0
11 Aug 2023
Monitoring Algorithmic Fairness under Partial Observations
Monitoring Algorithmic Fairness under Partial Observations
T. Henzinger
Konstantin Kueffner
Kaushik Mallik
MLAU
88
3
0
01 Aug 2023
Bipartite Ranking Fairness through a Model Agnostic Ordering Adjustment
Bipartite Ranking Fairness through a Model Agnostic Ordering Adjustment
Sen Cui
Weishen Pan
Changshui Zhang
Fei Wang
52
12
0
27 Jul 2023
On the Vulnerability of Fairness Constrained Learning to Malicious Noise
On the Vulnerability of Fairness Constrained Learning to Malicious Noise
Avrim Blum
Princewill Okoroafor
Aadirupa Saha
Kevin Stangl
74
2
0
21 Jul 2023
Towards Better Fairness-Utility Trade-off: A Comprehensive
  Measurement-Based Reinforcement Learning Framework
Towards Better Fairness-Utility Trade-off: A Comprehensive Measurement-Based Reinforcement Learning Framework
Simiao Zhang
Jitao Bai
Menghong Guan
Yihao Huang
Yueling Zhang
Jun Sun
G. Pu
FaML
46
1
0
21 Jul 2023
Learning for Counterfactual Fairness from Observational Data
Learning for Counterfactual Fairness from Observational Data
Jing Ma
Ruocheng Guo
Aidong Zhang
Jundong Li
FaML
55
12
0
17 Jul 2023
National Origin Discrimination in Deep-learning-powered Automated Resume
  Screening
National Origin Discrimination in Deep-learning-powered Automated Resume Screening
Changhao Nai
Kuangzheng Li
Haibing Lu
52
4
0
13 Jul 2023
Through the Fairness Lens: Experimental Analysis and Evaluation of
  Entity Matching
Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching
N. Shahbazi
Nikola Danevski
F. Nargesian
Abolfazl Asudeh
D. Srivastava
49
10
0
06 Jul 2023
Scaling Laws Do Not Scale
Scaling Laws Do Not Scale
Fernando Diaz
Michael A. Madaio
104
12
0
05 Jul 2023
Algorithms, Incentives, and Democracy
Algorithms, Incentives, and Democracy
E. M. Penn
John W. Patty
FaML
62
1
0
05 Jul 2023
Minimum Levels of Interpretability for Artificial Moral Agents
Minimum Levels of Interpretability for Artificial Moral Agents
Avish Vijayaraghavan
C. Badea
AI4CE
64
5
0
02 Jul 2023
On the Cause of Unfairness: A Training Sample Perspective
On the Cause of Unfairness: A Training Sample Perspective
Yuanshun Yao
Yang Liu
TDI
75
0
0
30 Jun 2023
Systematic analysis of the impact of label noise correction on ML
  Fairness
Systematic analysis of the impact of label noise correction on ML Fairness
I. O. E. Silva
Carlos Soares
I. Sousa
R. Ghani
29
2
0
28 Jun 2023
FAIRER: Fairness as Decision Rationale Alignment
FAIRER: Fairness as Decision Rationale Alignment
Tianlin Li
Qing Guo
Aishan Liu
Mengnan Du
Zhiming Li
Yang Liu
60
16
0
27 Jun 2023
Privacy and Fairness in Federated Learning: on the Perspective of
  Trade-off
Privacy and Fairness in Federated Learning: on the Perspective of Trade-off
Huiqiang Chen
Tianqing Zhu
Tao Zhang
Wanlei Zhou
Philip S. Yu
FedML
77
47
0
25 Jun 2023
Trading-off price for data quality to achieve fair online allocation
Trading-off price for data quality to achieve fair online allocation
M. Molina
Nicolas Gast
Patrick Loiseau
Vianney Perchet
58
4
0
23 Jun 2023
Auditing Predictive Models for Intersectional Biases
Auditing Predictive Models for Intersectional Biases
Karen Boxer
E. McFowland
Daniel B. Neill
29
2
0
22 Jun 2023
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup
  Fairness
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
Neil Menghani
E. McFowland
Daniel B. Neill
57
0
0
19 Jun 2023
Correcting Underrepresentation and Intersectional Bias for
  Classification
Correcting Underrepresentation and Intersectional Bias for Classification
Emily Diana
A. Tolbert
FaML
73
1
0
19 Jun 2023
Evaluating Superhuman Models with Consistency Checks
Evaluating Superhuman Models with Consistency Checks
Lukas Fluri
Daniel Paleka
Florian Tramèr
ELM
113
44
0
16 Jun 2023
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
Xiaotian Han
Jianfeng Chi
Yu Chen
Qifan Wang
Han Zhao
Na Zou
Helen Zhou
90
31
0
15 Jun 2023
Arbitrariness Lies Beyond the Fairness-Accuracy Frontier
Arbitrariness Lies Beyond the Fairness-Accuracy Frontier
Carol Xuan Long
Hsiang Hsu
Wael Alghamdi
Flavio du Pin Calmon
FaML
69
7
0
15 Jun 2023
Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairness Repair
  using AutoML
Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairness Repair using AutoML
Giang Nguyen
Sumon Biswas
Hridesh Rajan
FaML
103
14
0
15 Jun 2023
Are fairness metric scores enough to assess discrimination biases in
  machine learning?
Are fairness metric scores enough to assess discrimination biases in machine learning?
Fanny Jourdan
Laurent Risser
Jean-Michel Loubes
Nicholas M. Asher
FaML
53
5
0
08 Jun 2023
Reconciling Predictive and Statistical Parity: A Causal Approach
Reconciling Predictive and Statistical Parity: A Causal Approach
Drago Plečko
Elias Bareinboim
FaML
54
2
0
08 Jun 2023
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