Description: As the use of artificial intelligence (AI) becomes more common in research workflows, Research Ethics Boards (REBs) face a new challenge in fulfilling their mandate for research ethics review from the lens of the TCPS2 without being technical validators of the tools and infrastructures proposed by the Researcher.
This session will explore research ethics review principles and practices regarding how AI is being used across qualitative and quantitative research workflows, along with intersections with research data management (RDM) practices for working with sensitive data. Topics will include potential privacy concerns, including both individual and group-level risks, as well as key considerations for informed consent when human participant data is collected, processed, or analyzed using AI tools.
Finally, the session will review what guidance is currently available to support researchers in using AI responsibly. As well as the role of REBs in assessing AI-related technologies and the associated research ethics risks. This includes what falls within the scope of REB review and where additional support or expertise may be available, while highlighting how researchers can better anticipate, communicate, and mitigate ethical risks associated with their work.
Teachers: Lucy Shen (Digital Research Alliance of Canada), Victoria Smith (Digital Research Alliance of Canada)
Level: Introductory
Format: Lecture, Lecture+Hands-on
Certificate: Attendance
Prerequisites: None