Algorithmic Responsibility

Catalog description

This course is designed to critically evaluate the core, contemporary issues facing the application of big data algorithms. Through class discussions, case studies and exercises, students will learn to exercise ethical consideration towards the responsible management of predictive analytics and their pervasive role in some of society's more prominent institutions. Discussion will cover the implications of storing and sharing data, algorithmic transparency, uncovering bias in the models, measuring accuracy, data ownership, and governance. The course also provides background on the tenets of analytic tools, their interpretations and determinations in applied arenas. Respective of these concerns, we will look into ways of conceptualizing, objectively evaluating, and mitigating bias in algorithmic decision-making. In essence, students will develop and defend an informed perspective on where, when and how to act responsibly in the construction and maintenance of predictive algorithms in "real world" settings.