UT News, The University of Texas at Austin ; Machine ‘Unlearning’ Helps Generative AI ‘Forget’ Copyright-Protected and Violent Content
"When people learn things they should not know, getting them to forget that information can be tough. This is also true of rapidly growing artificial intelligence programs that are trained to think as we do, and it has become a problem as they run into challenges based on the use of copyright-protected material and privacy issues.
To respond to this challenge, researchers at The University of Texas at Austin have developed what they believe is the first “machine unlearning” method applied to image-based generative AI. This method offers the ability to look under the hood and actively block and remove any violent images or copyrighted works without losing the rest of the information in the model.
“When you train these models on such massive data sets, you’re bound to include some data that is undesirable,” said Radu Marculescu, a professor in the Cockrell School of Engineering’s Chandra Family Department of Electrical and Computer Engineering and one of the leaders on the project. “Previously, the only way to remove problematic content was to scrap everything, start anew, manually take out all that data and retrain the model. Our approach offers the opportunity to do this without having to retrain the model from scratch.”"
