Research Ethics Considerations for the use of Artificial Intelligence (AI) and Machine Learning (ML) in Health Research
Questions are emerging around the ethics associated with the use of big data, machine learning (ML), and artificial intelligence (AI) in health research. While efforts on the technical side of AI move forward, and institutional appetite for AI deployment within care settings increases, work remains around the frameworks, policy, and legislation in place for the ethical review and oversight of research involving AI and ML.
In the absence of established legal frameworks, policy, or practice standards that specifically guide research ethics review and oversight of AI and ML-enabled studies, it is imperative to build research ethics board (REB) capacity to anticipate and address issues uniquely associated with rapid advances in technological capabilities and novel applications. It is equally important for researchers and technologists applying AI within the health space to understand REB review requirements and considerations.
This discussion invites an interdisciplinary look at how algorithmic tools are designed and used in health research. The conversation will broach many of the crucial ethical issues surrounding AI applications such as privacy, bias, accountability, and autonomy in an accessible way so as to inform ongoing discussions related to the development of standards, cases, precedence, and resources to be used in REB decision-making processes.