Cover Image

A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Barr, Caleb J. S., Erdelyi, Olivia, Docherty, Paul D., Grace, Randolph C.
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fair Machine Learning in Healthcare: A Review
by: Feng, Qizhang, et al.
Published: (2022)

On The Fairness Impacts of Hardware Selection in Machine Learning
by: Nelaturu, Sree Harsha, et al.
Published: (2023)

Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making
by: Schoeffer, Jakob, et al.
Published: (2022)

When Fairness Metrics Disagree: Evaluating the Reliability of Demographic Fairness Assessment in Machine Learning
by: Alsayed, Khalid Adnan
Published: (2026)

Public Perceptions of Fairness Metrics Across Borders
by: Sasaki, Yuya, et al.
Published: (2024)

EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders
by: Luo, Lin, et al.
Published: (2024)

FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
by: Dai, Yucong, et al.
Published: (2025)

SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models
by: Wang, Zhihao, et al.
Published: (2024)

Fairness in Graph Learning Augmented with Machine Learning: A Survey
by: Luo, Renqiang, et al.
Published: (2025)

To Be Forgotten or To Be Fair: Unveiling Fairness Implications of Machine Unlearning Methods
by: Zhang, Dawen, et al.
Published: (2023)

A Multivocal Literature Review on Privacy and Fairness in Federated Learning
by: Balbierer, Beatrice, et al.
Published: (2024)

Fair Streaming Feature Selection
by: Duan, Zhangling, et al.
Published: (2024)

AI Fairness in Practice
by: Leslie, David, et al.
Published: (2024)

FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive Learning
by: Chen, Wei, et al.
Published: (2024)

Metric-Fair Prompting: Treating Similar Samples Similarly
by: Wang, Jing, et al.
Published: (2025)

Fairness in Federated Learning: Fairness for Whom?
by: Taik, Afaf, et al.
Published: (2025)

Tuning Derivatives for Causal Fairness in Machine Learning
by: Edström, Filip, et al.
Published: (2026)

Fair In-Context Learning via Latent Concept Variables
by: Bhaila, Karuna, et al.
Published: (2024)

Analyzing Fairness of Classification Machine Learning Model with Structured Dataset
by: Rashed, Ahmed, et al.
Published: (2024)

Improving LLM Group Fairness on Tabular Data via In-Context Learning
by: Cherepanova, Valeriia, et al.
Published: (2024)

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance?
by: Liu, Junhua, et al.
Published: (2024)

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
by: Han, Xiaotian, et al.
Published: (2023)

Fairness Amidst Non-IID Graph Data: A Literature Review
by: Zhang, Wenbin, et al.
Published: (2022)

Fair in Mind, Fair in Action? A Synchronous Benchmark for Understanding and Generation in UMLLMs
by: Zhao, Yiran, et al.
Published: (2026)

Kantian Deontology Meets AI Alignment: Towards Morally Grounded Fairness Metrics
by: Mougan, Carlos, et al.
Published: (2023)

Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
by: Laakom, Firas, et al.
Published: (2025)

AI-Driven Healthcare: A Review on Ensuring Fairness and Mitigating Bias
by: Chinta, Sribala Vidyadhari, et al.
Published: (2024)

The Illusion of Fairness: Auditing Fairness Interventions with Audit Studies
by: Sariola, Disa, et al.
Published: (2025)

FairPO: Robust Preference Optimization for Fair Multi-Label Learning
by: Mondal, Soumen Kumar, et al.
Published: (2025)

FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning
by: Kim, Woosung, et al.
Published: (2025)

FairMT: Fairness for Heterogeneous Multi-Task Learning
by: Hu, Guanyu, et al.
Published: (2025)

Fair CCA for Fair Representation Learning: An ADNI Study
by: Hou, Bojian, et al.
Published: (2025)

Price of Fairness in Short-Term and Long-Term Algorithmic Selections
by: Jabbari, Shahin, et al.
Published: (2026)

Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa
by: Asiedu, Mercy Nyamewaa, et al.
Published: (2023)

Where are the Humans? A Scoping Review of Fairness in Multi-agent AI Systems
by: Allmendinger, Simeon, et al.
Published: (2026)

Generating Synthetic Fair Syntax-agnostic Data by Learning and Distilling Fair Representation
by: Sikder, Md Fahim, et al.
Published: (2024)

Continuous Fair SMOTE -- Fairness-Aware Stream Learning from Imbalanced Data
by: Lammers, Kathrin, et al.
Published: (2025)

MESD: A Risk-Sensitive Metric for Explanation Fairness Across Intersectional Subgroups
by: Popoola, Gideon, et al.
Published: (2026)

Incentive-Aware Machine Learning; Robustness, Fairness, Improvement & Causality
by: Podimata, Chara
Published: (2025)

BiasGuard: Guardrailing Fairness in Machine Learning Production Systems
by: Cohen-Inger, Nurit, et al.
Published: (2025)