Latest Articles for Fairness

Learn how the TREx framework improves online shopping recommendations.

Media organizations create guidelines for responsible AI use in journalism.

A new method addresses privacy and fairness in regression models using innovative adjustments.

A method to enhance fairness in classification models for sensitive areas.

This study examines bias in Continual Learning models for medical imaging.

Examining fairness in reinforcement learning systems for ethical decision-making.

Examining how technology impacts mental health fairness and bias.

New method improves fairness in COVID-19 case predictions across racial groups.

This article discusses the impact of LLMs on e-commerce fairness.

AI professionals share their views on Trustworthy AI and its challenges.

This article discusses the importance of fairness in machine learning predictions.

Do advanced AI models align with human moral values?

Enhancing fairness in AI by involving domain experts in data generation.

A study on improving task allocation fairness for service providers and tasks.

A novel approach improves performance and fairness in federated learning.

Examining the link between local differential privacy and fairness in ML systems.

This article discusses the importance of data practices for fairness in machine learning.

This article discusses the manipulations and flaws of PD plots in AI fairness.

A new algorithm improves the verification of neural networks for reliability and fairness.

Investigating LoRA's effects on fairness across different groups in machine learning.

This study examines how joint measures assess fairness and relevance in recommender systems.

A new approach improves fairness in identifying hate speech across diverse groups.

An examination of how algorithm choices affect individuals in critical decisions.

A new method improves efficiency and fairness in warehouse picking operations with robots.

This article reviews the importance of fairness in exchange systems and suggests a new approach.

AI's growing role in recruitment raises concerns about bias and fairness.

Research reveals biases in object detection systems affecting safety in autonomous vehicles.

A look into stable partitions and their role in matching individuals based on preferences.

A practical method to improve fairness in algorithms without sacrificing accuracy.

A framework that detects anomalies in graphs while promoting fair treatment.

This research examines the fairness of self-supervised learning models across demographic groups.

Examining the role of randomization in creating fair machine learning systems.

Exploring the benefits of rule sets for ethical predictive modeling.

A new approach to measuring fairness in college admissions and credit assessments.

This article discusses fairness measurement in recommendation systems and proposes sampling methods.

Analyzing prediction accuracy across different communities for equitable health resource allocation.

Research shows how demographics shape fairness views in AI content moderation.

This paper discusses methods to ensure fairness in AI through self-supervised learning techniques.

A new framework tackles fairness conflicts in machine learning effectively.

Testing LLMs is essential for safe and effective AI applications.