CMPUT 200 - Ethics of Data Science and Artificial Intelligence

3 units (fi 6)(EITHER, 3-0-3)

This course focuses on ethics issues in Artificial Intelligence (AI) and Data Science (DS). The main themes are privacy, fairness/bias, and explainability in DS. The objectives are to learn how to identify and measure these aspects in outputs of algorithms, and how to build algorithms that correct for these issues. The course will follow a case-studies based approach, where we will examine these aspects by considering real-world case studies for each of these ethics issues. The concepts will be introduced through a humanities perspective by using case studies with an emphasis on a technical treatment including implementation work. Prerequisite: one of CMPUT 191 or 195, or one of CMPUT 174 or 274 and one of STAT 151, 161, 181, 235, 265, SCI 151, MATH 181, or CMPUT 267.

CMPUT 499 - Topics in Computing Science

3 units (fi 6)(VAR, VARIABLE)

This topics course is designed for a one on one individual study course between a student and an instructor. Prerequisites are determined by the instructor in the course outline. See Note (3) above.

CMPUT 605 - Topics in Computing Science

3 units (fi 6)(EITHER, 3-0-0)

MMA 609 - Responsible AI & Ethical Issues in Data Analytics

3 units (fi 6)(SECOND, 3-0-0)

This course focuses on the ethical and legal considerations in artificial intelligence (AI) and data analytics, fields that are evolving rapidly and prompting novel ethical and regulatory concerns. It will cover subjects such as data privacy, fairness in algorithms, interpretability, and accountability. Participants will be educated on the responsible and ethical application of AI and data analytics technologies. Restricted to students registered in the MMA Program. Non-MMA students require consent of home dept and the Masters Programs Office.