Lecture
This lecture discusses the concept of global data justice and the importance of a social justice approach to data governance. It explores the challenges of formalizing fairness in data algorithms, the need to treat individuals as unique entities, and the implications of different approaches to equality of outcome. The lecture also delves into the ethical considerations of algorithmic systems, such as the 'Mulching Proposal' and the use of AI for detecting sexual orientation. It addresses the intersection of data ethics, accountability, and the political responsibility of researchers, emphasizing the need for trust, ethics, and responsible data science in governing data technologies.