New research shows that people recognize more of their biases in algorithms' decisions than they do in their own -- even when those decisions are the same. Algorithms were supposed to make our lives ...
Algorithms are a staple of modern life. People rely on algorithmic recommendations to wade through deep catalogs and find the best movies, routes, information, products, people and investments.
A Stanford-led study of 4 million job applications reveals AI tools used by Fortune 100 companies systematically reject Black ...
In recent years, employers have tried a variety of technological fixes to combat algorithm bias — the tendency of hiring and recruiting algorithms to screen out job applicants by race or gender. They ...
One of the largest studies on AI hiring algorithms found substantial evidence of bias and an adverse impact on specific ...
Artificial intelligence (AI) algorithms have become integral to our modern lives, influencing everything from online ads to recommendations on streaming platforms. While they may not be inherently ...
Get the latest federal technology news delivered to your inbox. Two Democratic senators are asking leadership in the Biden administration to do more to mitigate risks of artificial intelligence ...
Across the country, algorithms are shaping decisions about who gets hired, who advances, and who is filtered out, often before a hiring manager ever takes a closer look. What began as an efficiency ...
Algorithms were supposed to remake the American justice system. Championed as dispassionate, computer-driven calculations about risk, crime, and recidivism, their deployment in everything from ...
2022 might be remembered as the year that generative AI blasted on the scene, causing major waves in the digital community. With the onset of any new game-changing tech, in this case, the extremely ...
Algorithms were supposed to make our lives easier and fairer: help us find the best job applicants, help judges impartially assess the risks of bail and bond decisions, and ensure that health care is ...
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