Paradoxes are a class of phenomena that arise when, although starting from premises known as true, we derive some sort of logically unreasonable result. As Machine Learning models create knowledge from data, this makes them susceptible to possible cognitive paradoxes between training and testing. In this talk, Pier Paolo Ippolito will walk you through some of the main paradoxes associated with Data Science and how they can be identified.