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Generative artificial intelligence (Gen-AI) powered technologies are increasingly integrated across virtually all fields, including oncology, poised to fundamentally transform human-machine interaction (HMI). In biomedicine and oncology, Gen-AI tools are forming the foundation for intuitive patient-facing and clinician-facing interfaces that increase accessibility and efficiency of health care applications, enhance patient experience, and improve clinical workflows, ultimately optimizing patient outcomes. Despite Gen-AI's great potential in health care, limitations related to data quality and learning algorithms can create persistent challenges to patient safety, warranting a thorough HMI evaluation by end-users and experts that goes beyond traditional statistical validation. In parallel, a legal framework for assigning liability among developers, deployers, maintainers, and end-users is essential to ensure fairness and promote safe and beneficial application of clinical AI.
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Niraula et al. (2025) studied this question.
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