BLG 553E - Special Topics in Compu.Eng. - Trustable AI

Course Objectives

Have a through understanding of what makes an AI system trustable.

Course Description

Machine Learning models and solutions based on them are increasingly operationalized. This course will cover how to evaluate, communicate, update trustworthiness of a machine learning solution. Trustworthiness will be evaluated under validity, privacy, explainability and responsibility components. AI interpretation methods will be covered in depth. Applications in different industries will be examined. Students will need prepare a project where they help an AI to become more trustworthy through one or more of the aspects above. Python programming and Machine Learning or an equivalent course are prerequisites.