“The roots of algorithmic bias can be technically very complex,” says Luca Trevisan, a Professor of Bocconi's newly established Department of Computing Sciences, “and it is therefore difficult to discuss it apart from the technical aspects. STEM disciplines can model discrimination mathematically and can identify problems and possible solutions.”