Over the past couple of decades, computer scientists have developed a wide range of deep neural networks (DNNs) designed to tackle various real-world tasks. While some of these models have proved to be highly effective, some studies found that they can be unfair, meaning that their performance may vary based on the data they were trained on and even the hardware platforms they were deployed on.
How hardware contributes to the fairness of artificial neural networks
Reader’s Picks
-
“Birthrates are plummeting worldwide. Can governments turn the tide?” “The world is running out of children as global birth rates [...]
-
Scotland’s care system is taking years to find many of the country’s most vulnerable children permanent homes—and too many of [...]
-
Social media is negatively impacting the life satisfaction of Australian high school students, according to the latest findings from Australia’s [...]