AI & Data Ethics
This course introduces students to the ethical issues that emerge in Data Science and the related field of Artificial Intelligence.
It introduces students to the main ethical concepts and values shaping the current debates of data and AI and data ethics, including gaining an understanding of the philosophical background, the history of such debates, the relevance of professional ethics and of the ethics of research on the human subject, and the current regulatory and policy landscape.
Students will examine the production, collection, storing, curation and sharing of data as well as the context of the construction and evaluation of models and hypotheses using AI.
They will learn how to apply abstract ethical concepts to practical uses in the analysis of cases and in the production of policy for these ongoing debates. Students will also be encouraged to consider how issues raised in a technological context may be illuminated by considerations from a wide range of disciplines, including literature and the social sciences.
- Ethical frameworks for AI: concepts, policy and regulation landscapes for AI and data ethics
- Transparency and explainability in machine learning and AI
- Data privacy, data ownership, and the digital self
- Bias of algorithms and fairness in the use of AI
- Access to and control over information, governance of social media
The following degrees contain this course: