Development of AI/ML REB review tools at BC Cancer: A collaborative multi-disciplinary approach

DESCRIPTION OF SESSION

As Artificial Intelligence (AI) and Machine Learning (ML) techniques become rapidly prominent in the research landscape, Research Ethics Boards (REBs) nationally are reshaping their review processes and considerations to address the growing breadth of ethical considerations in applying AI/ML to human data. In a rapidly evolving research landscape, AI/ML techniques are currently being integrated into research and applied to human data at an unprecedented rate. The REB must remain empowered to target critical concerns in order to ensure a comprehensive understanding and identification of the unique ethical implications that AI/ML can pose to our patient population and healthcare system. BC Cancer's REB has adopted a proactive strategy to address the recent rise in the number of AI/ML-based research ethics applications. We will discuss the development of BC Cancer's AI/ML review tools used by both researchers and REB members which streamline and standardize the process of evaluating AI/ML-based research. We will identify and explore the challenges and strategies involved in managing these reviews, including re-evaluating the REBs role in AI/ML reviews and the review model adapted to collaborate with AI/ML experts in overseeing the review of these research applications. This session will highlight how an adaptable and informed REB can navigate an evolving research landscape to address ethical oversight with the use of collaborative AI/ML review tools. Please come prepared with thoughts or questions regarding AI/ML-based research ethics during the collaborative portion of this session.