Governing artificial intelligence in cancer care: Perspectives and recommendations from patient organizations and the MULTIR consortium

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BackgroundArtificial intelligence (AI) has the potential to improve cancer care. Its implementation must align with patients’ needs, values, and lived experiences. This study aimed to explore perspectives from representatives of patient organizations, including individuals with experience of melanoma, bladder and lung cancer and to co-develop recommendations to support the ethical, patient-centered, and practical integration of AI in oncology.MethodsSemi-structured interviews were conducted with 18 representatives of patient organizations within the MULTIR consortium network to explore current challenges in cancer care, perceptions of the benefits and risks of AI, and conditions for its trustworthy, sustainable and equitable adoption. Findings were reviewed and refined through a series of webinars, enabling participants to validate and strengthen the resulting recommendations.ResultsParticipants identified key benefits and risks associated with AI and formulated six main recommendations targeting developers, policymakers, regulators, and researchers. These include: ensuring clear, accessible, and transparent communication about AI; strengthening training and capacity-building for healthcare professionals and patient organizations; demonstrating tangible clinical and patient-level benefits; developing secure, robust, and interoperable data infrastructures; reinforcing ethical and regulatory frameworks; and ensuring the sustained and meaningful involvement of patient organizations throughout AI development, implementation, and evaluation processes.ConclusionThese recommendations provide actionable, patient-informed directions for advancing the integration of AI in cancer care. Although grounded in insights from specific cancer communities, they are broadly applicable across oncology. Progress will require the structured integration of patient organizations and experiential knowledge into governance, research, and implementation processes, in order to support more equitable, trustworthy, and patient-centered AI-enabled health systems.Policy SummaryThe recommendations have implications for European policies on healthcare regulation, digital health infrastructure, and data governance. They highlight the importance of capacity building, stakeholder engagement, and embedding principles of equitable access, responsible implementation, and patient-centered governance in AI-enabled health services.