We are finally witnessing increasing adoption of digital pathology in clinical practice. Pathologists are beginning to embrace and utilize artificial intelligence (AI) tools and ideas to augment routine pathology practice. All stakeholders in pathology need to fully understand the ethical frameworks required to develop, deploy, and maintain transparent, trustworthy, explainable, scalable, interoperable, and sustainable digital AI tools. Read more
The three largest concerns around the ethics of AI/ML in artificial intelligence human subject research are explainability, identifiability, and algorithmic bias. It is imperative that IRBs understand the AI/ML’s explainability in order to fulfill their responsibility of adequately assessing the risk-benefit ratio in AIHSR. Read more
In April, the Food and Drug Administration (FDA) issued a discussion paper, "Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD).” The paper represents FDA’s response to the growing number of medical device manufacturers who are utilizing artificial intelligence and machine learning technologies to continuously improve their products. On June 3, PRIM&R submitted comments in response to the discussion paper, thanking the FDA for their consideration of the public health implications of the use of these technologies, but also cautioning that any new regulatory approach in this area must address the protection of individuals whose personal information and data are being used in the creation and ongoing testing of these technologies. Read more
