The problem of “filter bubbles” – a phenomenon caused by social network AI algorithms recommending to their users only the kind of content they will like or agree with – has been well documented in the past few years. But could AI itself provide the solution to this problem? Jonathan asks Robert Moro, an AI expert at the Kempelin Institute in Bratislava, about whether AI algorithms could be designed instead to recommend content from a variety of points of view, in order to counteract the troubling social effects of filter bubbles.