The era of behavioural big data has created new avenues for data science research, with many new contributions stemming from academic researchers. Yet data controlled by platforms, such as Facebook, Tiktok or Youtube, have become increasingly difficult for academics to access. Authors Travis Greene, David Martens and Galit Shmueli discuss the consequences, and encourage academics to take on new roles in promoting platform transparency and public debate.
Big Data generated by people provide enormous prediction value for Artificial Intelligent systems. However, explaining how these models use the data to make predictions is quite challenging. This Evidence Counterfactual explanation approach considers how a model would behave if it didn’t have the original set of data to work with.