In a new review, Yale researchers provide an in-depth analysis of how biases at different stages of AI development can lead to poor clinical outcomes and exacerbate health disparities. The authors say their results reflect an old adage in the computing world: “Garbage in, garbage out.”
‘Bias in, bias out’: Study identifies bias in medical AI
Tech News
-
Free Dark Web Monitoring Stamps the $17 Million Credentials Markets
-
Smart buildings: What happens to our free will when tech makes choices for us?
-
Screenshots have generated new forms of storytelling, from Twitter fan fiction to desktop film
-
Darknet markets generate millions in revenue selling stolen personal data, supply chain study finds
-
Privacy violations undermine the trustworthiness of the Tim Hortons brand
-
Why Tesla’s Autopilot crashes spurred the feds to investigate driver-assist technologies – and what that means for the future of self-driving cars