BT08 Mapping UK frameworks for ethical artificial intelligence applied to dermatology

Abstract There is significant enthusiasm to apply artificial intelligence (AI) in dermatology with an emphasis on image-based analyses for risk assessment of suspicious skin lesions. However, the rapid development and deployment such AI tools raises concerns that ethical issues arising from their widespread, long-term use may not have been adequately considered during design or implementation. Dermatology, particular, has identified as lacking sufficient bioethics research could standardize approach regulating AI-assisted applications. Despite efforts develop robust guidelines ‘ethical AI’ across private, national international organizations, debate continues surrounding which principles should be included. The 2022 National Strategy positions UK leading global toward achieving safe AI. We sought systematically review analyse policy documents map promoting applied dermatology. Our five relevant published between 2016 2022. All included frameworks highlighted importance upholding transparency fairness along entire lifecycle decision-making. also incorporated autonomy through reference maintaining informed consent, data privacy human contestability decisions. accountability nonmaleficence were each four documents, emphasizing needs clear definitions legal organizational responsibility thorough testing avoid unintended/unwanted outcomes. beneficence (designing promote good both individual societal levels) sustainability (continually monitoring adjusting longevity efficacy) two documents. Current converge around key values: fairness, transparency, autonomy, accountability. advanced, although less frequently highlighted. a reassuring level convergence practical implementation these health care particularly skin-specific remains unclear. Furthermore, evidence real-world integration into developing AI-based cancer diagnostic lacking. Future work seeks address this gap by analysing commercially available applications using predefined themes identify case-specific evaluate extent are addressed within existing frameworks. This will provide guidance developers adopters tools, ensuring responsible deployment.