Please note: This master’s thesis presentation will take place online.
Carolyn Wang, Master’s candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Maura Grossman, Dan Brown
Canada suffers from a mental health crisis, with mental health care that is very difficult to access despite widespread demand. This has prompted significant interest in applying artificial intelligence (AI) to improve the accessibility and efficacy of care. Simultaneously, scholars emphasize the importance of ensuring the safety and ethicality of such technologies through various methods.
This thesis first audits a large language model for identity-based bias in patient mental health assessment tasks, which has received significant attention in the literature. We then turn to explore the attitudes of mental health clinicians on the use of AI in their work, with an emphasis on the effect of AI literacy on participants’ perceptions. We conduct a mixed-methods interview study to examine clinicians’ current uses of AI and attitudes towards AI integration. We also investigated how increased AI literacy affects these views by measuring participant perceptions before and after delivering an educational intervention. Using both qualitative and quantitative analysis methods, we analyzed data from questionnaires and interview transcripts.
Our results uncover a number of ways that clinicians are already using AI to support their work and strategies they employ to safeguard against the risks of such uses. Furthermore, our qualitative analysis elicits a set of eight factors informing clinicians’ attitudes towards the integration of AI into mental health care, forming a framework through which to analyze AI tools for mental health. Our quantitative analysis shows the effect of AI literacy on participatory studies such as this one; augmented by further qualitative analysis, our results demonstrate the importance of greater AI literacy in participatory research with non-technical communities. The results of this research may help to inform further collaborative research efforts seeking to apply technology to address the mental health crisis.