Teaching Responsible Machine Learning to Engineers

Hilde Jacoba Petronella Weerts, Mykola Pechenizkiy

Keywords: machine learning, education, ethics, fairness

TL;DR: We reflect upon the development of a course on responsible machine learning targeted at undergraduate engineering students.

Abstract: With the increasing application of machine learning models in practice, there is a growing need to incorporate ethical considerations in engineering curricula. In this paper, we reflect upon the development of a course on responsible machine learning for undergraduate engineering students. We found that technical material was relatively easy to grasp when it was directly linked to prior knowledge on machine learning. However, it was non-trivial for engineering students to make a deeper connection between real-world outcomes and ethical considerations such as fairness. Moving forward, we call upon educators to focus on the development of realistic case studies that invite students to interrogate the role of an engineer.