If a machine-learning model is trained using an unbalanced dataset, such as one that contains far more images of people with lighter skin than people with darker skin, there is serious risk the ...
A recent study in Nature Machine Intelligence by researchers at Carnegie Mellon sought to investigate the impact that mitigating bias in machine learning has on accuracy. Despite what researchers ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More LinkedIn today released the LinkedIn Fairness Toolkit (LiFT), an open ...
Editor’s note: Deep Dive – a feature looking in depth at timely issues from tech to jobs is a regular feature on Wednesdays in TechWire. CHAPEL HILL – The recent explosion of large language models ...
Bias in algorithms have always been a key issue in the growing field of artificial intelligence. For instance, researchers found in an experiment that flawed AI in robots has the tendency to make ...
AI researcher Anmol Aggarwal explains how fairness-aware pricing algorithms can reduce hidden bias without major revenue loss ...
Scientists have introduced a new framework for designing machine learning algorithms that make it easier for users of the algorithm to specify safety and fairness constraints. Seventy years ago, ...
Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...
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