Training artificial intelligence to enforce even seemingly straightforward rules – like balls and strikes in Major League Baseball – is a messy, dynamic process that takes time and careful evaluation of the technology.
For consequential decision-making, the benefits of a simple index score vs. a less-interpretable predictive AI algorithm depend, researchers from Cornell found, on the desired outcome as well as the decision’s intended audience.
On July 1, the digital research respository arXiv, housed at Cornell Tech, will transition to an independent nonprofit, enabling faster technological development, expanded partnerships and long-term financial sustainability.
Cornell information science researchers have developed a method that can help online advertisers ensure they’re reaching their intended audience and reduce “skew” – under-delivery to certain demographic groups.
Artificial intelligence may one day give robots social intelligence, but so far, existing models do a poor job of using human facial cues to predict the outcome of a situation.
Researchers at Cornell Tech and Cornell Bowers have created an AI framework that can create “shadow art” – partial line drawings that are completed by the shadow cast from an object – by simply scanning the object.
