Latest Articles for Fairness

Addressing fairness challenges in systems influenced by human preferences and behaviors.

Examining biases in AI-driven resume screening and ways to improve fairness.

Explore how Shapley values clarify machine learning predictions in healthcare.

This article examines the trade-off between fairness and overall satisfaction in resource division.

This article discusses the issues and strategies for implementing Responsible AI values.

Exploring fairness in selecting representatives from diverse groups.

A look at promoting fairness in recommendation systems amidst information overload.

Integrating explainable AI into 6G enhances user trust and performance.

This article examines fairness issues in facial recognition technology.

Examining concerns of test-takers regarding AI versus traditional human scoring.

Examining bias in machine learning code reviewer systems.

A new method for improved fairness in federated learning client selection.

This article discusses creating fair hashmaps for equitable data management.

A new framework enhances fairness in algorithms using uncertain demographic information.

Investigating fairness in ML systems considering multiple protected attributes.

A four-step method to promote ethical AI development across various roles.

Discover how RIS technology improves communication efficiency and fairness in future networks.

New tools aim to enhance fairness in AI by providing access to diverse datasets.

A new framework to ensure fairness in AI systems while in operation.

A new method improves model fairness by generating synthetic data samples.

This study reveals biases in how autonomous cars detect pedestrians based on age and skin tone.

This paper examines counterfactual invariance and its connections to conditional independence.

A look at multicalibration and omniprediction in machine learning.

Exploring fairness in DLTs, particularly through the lens of DAG-based systems.

This study introduces a method to reduce bias in machine learning models.

A look at how campaigns use data to influence district fairness.

RIFO optimizes packet scheduling for efficient data flow in networks.

A framework for creating fair and inclusive smart devices.

A new method improves fairness in generative models without requiring original datasets.

New methods aim to improve calibration in risk prediction models across diverse groups.

Understanding how AI improves clinical risk prediction and trust.

This framework combines fairness and robustness for responsible AI systems.

Research explores balance in multilingual language models for fairness and privacy.

New interventions seek to reduce bias in GNNs while maintaining accuracy in predictions.

This work introduces innovative techniques for managing complex reactive programs effectively.

Research reveals harmful stereotypes in language models toward marginalized groups.

This article discusses fairness in clustering, focusing on the Minimum Bisection problem.

A new model aims to reduce health disparities in electronic records.

Research shows how machine learning models can improve accuracy across varied patient groups.

Learn about the systems behind lottery ticket designs and their significance.