Fair Prediction

Fair prediction in machine learning aims to create models that make accurate predictions without exhibiting bias against specific demographic groups. Current research focuses on incorporating causal inference and counterfactual fairness into model development, employing techniques like constrained optimization and novel loss functions to balance accuracy and equity across subgroups. This work is crucial for mitigating societal harms stemming from biased algorithms, impacting fields like healthcare, criminal justice, and climate modeling by ensuring fairer and more equitable outcomes. Prominent approaches involve adapting transformer architectures and leveraging techniques from representation learning and federated learning to achieve fairness across diverse datasets and settings.

Papers

July 8, 2024

FairPFN: Transformers Can do Counterfactual Fairness
Jake Robertson, Noah Hollmann, Noor Awad, Frank Hutter
Transformer Megatron Decepticons Causal Effect Causal Model Counterfactual Fairness Fair Prediction Fair Synthetic

June 28, 2024

Enforcing Equity in Neural Climate Emulators
William Yik, Sam J. Silva
Biased Prediction Equity Context Fair Prediction Hyperparameter Importance Climate Model Emulation

January 19, 2024

Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach
Aoqi Zuo, Yiqing Li, Susan Wei, Mingming Gong
Causal Inference Causal Graph Constrained Optimization Fairness Intervention Causal Fairness Causal DAG Fair Prediction

November 30, 2023

Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
Maresa Schröder, Dennis Frauen, Stefan Feuerriegel
Biased Prediction Fairness Method Unmeasured Confounding Causal Fairness Fair Prediction Sensitivity Sampling

October 9, 2023

On Prediction-Modelers and Decision-Makers: Why Fairness Requires More Than a Fair Prediction Model
Teresa Scantamburlo, Joachim Baumann, Christoph Heitz
Procedural Fairness Predictive Model Algorithmic Fairness Decision Maker Fair Predictor Fair Prediction Prediction Based Decision Making

September 11, 2023

Re-formalization of Individual Fairness
Toshihiro Kamishima
Fairness Notion Individual Fairness Fairness Aware Machine Equalized Odds Fair Prediction

July 17, 2023

Learning for Counterfactual Fairness from Observational Data
Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
LeArning Abstract Observational Data Causal Discovery Method Counterfactual Fairness Fairness Aware Machine Fair Prediction

June 27, 2023

FAIRER: Fairness as Decision Rationale Alignment
Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li, Yang Liu
Deep Neural Network Procedural Fairness Rationale Alignment Fairness Regularization Fairness Loss Fair Prediction Neuron Alignment

February 17, 2023

The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction
Falaah Arif Khan, Julia Stoyanovich
Context Information Gaussian Mixture Model Bias Variance FAir Classifier Conditional Model Bias Variance Decomposition Fair Prediction Weight Monitoring Privileged Feature

January 29, 2023

Fair Decision-making Under Uncertainty
Wenbin Zhang, Jeremy C. Weiss
Procedural Fairness High Uncertainty Anticipation Fairness Constraint Fairness Notion Algorithmic Decision Fair Decision Fair Prediction

October 19, 2022

On Learning Fairness and Accuracy on Multiple Subgroups
Changjian Shui, Gezheng Xu, Qi Chen, Jiaqi Li, Charles Ling, Tal Arbel, Boyu Wang, Christian Gagné
Bilevel Optimization Fair Predictor Fair Learning Fair Prediction Subgroup Description Fairness Learning

July 18, 2022

When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes
Canyu Chen, Yueqing Liang, Xiongxiao Xu, Shangyu Xie, Ashish Kundu, Ali Payani, Yuan Hong, Kai Shu
Procedural Fairness Privacy Policy Local Differential Privacy Sensitive Attribute Fair Classification Fair Prediction

June 13, 2022

A Machine Learning Model for Predicting, Diagnosing, and Mitigating Health Disparities in Hospital Readmission
Shaina Raza
Machine Learning Model Human Prediction Medical Diagnosis Health Disparity Clinical Data Healthcare Datasets Fairness Measure Fair Prediction Hospital Readmission

March 18, 2022

Fair Federated Learning via Bounded Group Loss
Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith
Group Fairness FAIR Federated Learning Group Fairness Constraint Group Loss Fair Prediction