Latest Articles for Fairness

Analyzing decision-making and fairness through the lens of the Ultimatum Game.

This article discusses the need for clarity in machine learning models.

Conference discusses fairness across image upsampling techniques and racial representation.

Examining biases in predictive models for real estate pricing using geospatial data.

This study questions the preference for AUPRC over AUROC in imbalanced datasets.

Researchers are developing synthetic voice data to protect privacy in voice recognition.

Examining the fairness of recommendations made by algorithms after negative outcomes.

This article explores new wireless technologies to improve connectivity for users.

Exploring how digital tools can enhance citizen engagement and trust in democracy.

Examining fairness challenges in GNNs amidst changing data distributions.

This article discusses the impact of data under-reporting on fairness in predictive models.

Exploring ways to enhance trustworthiness in distributed artificial intelligence technologies.

A new method balances fairness for consumers and producers in recommendations.

Integrating Foundation Models with Federated Learning presents both risks and benefits.

A strategy to enhance performance and fairness in federated learning models.

A study on efficient task assignment while considering budgets and conflicts.

A model for fair and efficient electric bus charging infrastructure planning.

Exploring methods for fair ranking in various applications.

A fresh approach to ensure AI systems are reliable and safe.

Introducing an efficient algorithm for fair clustering of large datasets.

Strategies for fair water distribution in agriculture amidst growing scarcity.

Exploring the key ethical concerns in AI development and usage.

This research focuses on reducing multiple biases in language models simultaneously.

Exploring fairness issues in machine learning and federated systems.

This article explores how causal learning enhances recommender systems' fairness and reliability.

A new framework prioritizes fairness in crowdsourced machine learning competitions.

A look at the need for fairness and clear explanations in AI systems.

Study shows AI affects fairness, trust, and cooperation in social interactions.

A system to check fairness in machine learning while protecting model privacy.

Examining fairness and efficiency in distributing limited resources.

Partnerships aim to develop fair AI tools for global healthcare improvement.

A new method ensures fair exposure of items in recommendation systems.

A look at improving recommender systems for fairness and user satisfaction.

Strategies to reduce bias in ML, focusing on continuous sensitive attributes.

Examining bias in deep learning for MRI image reconstruction across gender and age.

Explore fair allocation of chores among agents with different responsibilities.

This article discusses explainability and fairness in legal judgment prediction models.

A new tool assesses bias in ML-based early-warning systems for better patient care.

This study examines how pooling data can enhance model fairness across diverse groups.

Discussing privacy and fairness in machine learning through differential privacy and worst-group risk.