Risk-based approaches to governance bear an ambiguous stance regarding the R&D stages of AI, for they the possibility of explicit risks before they are posed by a given finalised product. In this context, Institutional Review Boards (IRBs) stand as unique governance mechanisms, capable of addressing the step from general research to concrete product development. However, IRBs face several challenges in governing AI-based medical products, including: (a) achieving consistency, (b) being exhaustive, (c) ensuring process transparency, and (d) reducing the existing capacity and knowledge asymmetry between different stakeholders. This article explores four governance levers that can be used to effect change, four governance entry-points throughout a product’s lifecycle, and five different behaviours that IRBs should try to advance to ensure the effective governance of the R&D stages of AI-based medical projects. In doing so, IRBs can seize the unique opportunity they present to bring principles into practice, increase research quality, reduce governance costs, and bridge the knowledge gap between stakeholders.
Keywords: AI governance; research and development; risk-based approach; research ethics