Privacy-preserving and Ethical Analysis of Big Data

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The recent explosion of the amount and diversity of data, often refer to as Big Data, offers the possibility to realize inferences with an unprecedented level of accuracy and its analysis holds many promises in terms of knowledge, innovation and societal benefits. However, it also raises serious ethical issues among which privacy is a central one. The transparency, accountability and fairness of the model learnt from Big Data should also be enforced. The proposed Canada Research Chair will address these concerns by focusing on the conception of novel privacy-preserving and ethical methods for the analysis of Big Data. Another objective of the chair is to gain an in-depth understanding of the interactions between the concepts of privacy, fairness and explainability when elaborating machine learning models and to use this knowledge to guide their application in the context of high-stake decision systems.