"I realized two things It’s doable at the massive scale of the campaign, and that means it’s doable in the context of other problems.”"
Rayid Ghani is a Distinguished Career Professor in the Machine Learning Department and the Heinz College of Information Systems and Public Policy at Carnegie Mellon University. Previously, he was the director of the Center for Data Science and Public Policy, research associate professor in the department of computer science, and a senior fellow at the Harris School of Public Policy at the Universi
"So I think the way to think about it isnt whether its going to help or not, or does it do something well or not, but does it do it better than what were doing today? And I think that gets to deepest point of values. If we take a problem and we solve it and now its 90% correct, well what does that mean? Do we only care about overall correctness, or do we care about how does it have disparate impact on different types of people? If its 10% wrong, is it 10% wrong on everybody"
"One thing I think we should realize is, well be calling the AI today what they used to call AI 10 years ago. AI 10 years ago was a bunch of rules. You would write thousands of rules and that was AI. And thats embedded in pretty much every system we consume today. Every service were getting-- simple things like health insurance. A typical high-rate insurance company has about half a million rules inside the system to process your claim. And so AI has always been in there; its just as soon as it becomes deployed, its not called AI because its now real, its not magic."