Big Data Justice: A Case for Regulating the Global Information Commons

The advent of artificial intelligence (AI) challenges political theorists to think about data ownership and policy makers regulate the collection use public data. AI producers benefit from free for training their systems while retaining profits. We argue against view that must be free. proponents unconstrained point out consuming does not diminish its quality information is in ample supply. Therefore, they suggest, publicly available should present two objections. First, allowing promotes unwanted inequality. Second, contributors did could anticipate contribution would used train systems. Our argument implies managing “global commons” charging extensive permissible desirable. discuss implications propose a progressive tax counter inequality arising.