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Cloud-based machine learning systems are increasingly used in sectors such as healthcare, finance, and public services, where they influence decisions with significant social consequences. While …
Artificial intelligence systems deployed through cloud infrastructure have transformed numerous sectors while simultaneously raising critical ethical concerns regarding bias and fairness. This article examines the …
This paper examines how UK ‘hard laws’ can adapt to regulate algorithmic bias in the healthcare context. I explore the causes of algorithmic bias which …
Machine learning fairness enhancement methods based on data bias correction are usually divided into two processes: The determination of sensitive attributes (such as race and …
AI-driven healthcare systems perpetuate gendered and racialised health inequalities, misdiagnosing marginalised populations due to historical exclusions in medical research and dataset construction. These disparities are …
The rapid integration of artificial intelligence (AI) into critical decision-making domains—such as healthcare, finance, law enforcement, and hiring—has raised significant ethical concerns regarding bias and …
PurposeThis study examines the impact of data bias and algorithmic discrimination on individual credit accessibility in China’s financial system. It aims to align financial inclusion …
Home Submit GLJ Online 112 Student Notes Contest 112 Student Notes Contest The Georgetown Law Journal & GLJ Online present the winner of the fourth …
NeurIPS 2025 Expo Call NeurIPS is soliciting applications for the EXPO (Talks, panels, demonstrations, workshops, and active training classes) from Diamond & Platinum exhibitors.The NeurIPS …
NeurIPS 2025 Mexico City – Call for Startup Pitch We’re thrilled to announce the Startup Pitch Competition at the Mexico City satellite location of NeurIPS …
San Diego Mexico City NeurIPS 2025 @ San Diego Convention Center San Diego Convention Center Map Start Here Everyone is expected to follow the Code …