Perspectives On Machine Learning and Artificial Intelligence from Trainee Radiologists
Abstract:
Machine learning and artificial intelligence systems are ubiquitous across modern life, but various demographics and disciplines approach and perceive it differently. This MSc project examines the perceptions of qualified clinicians at the beginning of their radiology training with regards to machine learning and AI both personally and professionally, to gain a deeper insight into how technology affects their working lives. We designed a semistructured workshop in collaboration with the National Imagining Academy of Wales to survey a new intake of students to examine their emotional and academic understandings of machine learning. This workshop was broken into three different sections, examining ML in daily life, ML in the workplace, and the future implications and impacts of ML on their careers as radiologists. To examine these sections, we utilized a variety of methods including freeform discussion and personal reflection, quantitive scoring and ranking of tasks, and design fiction and futurism.
We analysed this data by hand by deconstructing audio recordings of the workshop and examining thematic content that was consistently found throughout the course of the study. What this project found was that our participants had a good understanding of the basics of machine learning technology, and had openly positive beliefs about the impact that the increasing implementation of artificial intelligence and automation would have on their careers. However, we also found that there seemed to be a more inherent skepticism of trusting machine learning systems in more high-pressure environments, and there were misconceptions regarding how these algorithms find and utilize data to provide their results.
We believe that this project can be used to examine how clinicians are educated regarding machine learning and artificial intelligence, and may trigger re-considerations on the way that these systems are designed and implemented in the field of radiology.
Rory Clark