Human judgment is key to AI fairness: study finds

AI-supported recommendation systems are intended to provide users with the best possible suggestions for their queries. These systems often have to serve different target groups and take into account other stakeholders who also have an influence on the machine’s reaction: e.g. E.g. service providers, municipalities or tourism associations. So how can a fair and transparent recommendation be achieved here? Researchers from the Graz University of Technology (TU Graz), the Karl-Franzens University of Graz and the Know Center investigated this using a bike tour app from the Graz start-up Cyclebee. They investigated how the diversity of human needs can be taken into account through AI. The study, which was awarded the Mind the Gap research prize for gender and diversity by Graz University of Technology, was funded by the Styrian Future Fund.

Impact on numerous groups

“AI-supported recommendation systems can have a major influence on purchasing decisions or the development of guest and visitor numbers,” says Bernhard Wieser from…