Kings College, U.K. 2. The Role of Patientsmedical AI. However, their approaches to the associated challenges differ significantly, reflecting institutional and cultural differences. This report compares Japan and the UK with a particular focus on the positioning of patients and the evaluation of the AI implementation in healthcare. The first key difference lies in how patients are positioned in the implementation of the medical AI.In discussions surrounding the introduction of the medical AI, patients in Japan are often regarded not as autonomous decision-makers, but rather as passive providers of data or mere recipients of services.There is a noticeable lack of perspective on how patients themselves engage with or make choices regarding their care, and both institutional and technological frameworks tend to be designed primarily from the viewpoints of physicians, administrators, and developers. According to the Ministry of Health, Labour and Welfare in Japan, the explanation of patients’roles is limited to providers of data and recipients of services. Patients’rights to make decisions regarding the AI use or the necessity of explanation are not indicated, suggesting that patients’perspectives may be underrepresented in the AI adoption. Thus, institutional design in Japan positions patients in a passive role for three main reasons; 1) there is no explicit recognition of patients’rights to choose, refuse, or appeal; 2) patients are not assumed to be active participants; and 3) the system is primarily constructed from the perspectives of healthcare professionals, administrators, and developers. In contrast, the UK takes the stance where the ultimate decision to use the AI lies with the patients. The British Medical Association (BMA) emphasises that patients should have the right to decide whether the AI is used in their care, to refuse the AI involvement, and to object to diagnosis or recommendations from the AI. The UK recognises the principle that patient autonomy and the right to choose must be protected. The use of Artificial Intelligence (AI) in healthcare has been expanding in recent years. Common applications include the AI-assisted image diagnosis, pharmaceutical development, and support for diagnosis and treatment. Implementation of the AI in clinical settings benefits through more accurate diagnosis, prediction, risk assessment and relieving medical practitioners' workload. The potential disadvantages include the risk of misdiagnosis, insufficient transparency, ambiguous accountability, bias, and privacy concerns.Figure 1. Forecast of the AI in healthcare Market Growth: Japan, the UK, and the World (2023–2030)Figure 2. Comparison of CAGR (Compound Annual Growth Rate): 2023–2030Grand View Research (2024) As shown in Figures 1 and 2, the AI in healthcare markets in both Japan and the UK are expected to grow steadily, with both countries exceeding the global average growth rate. Therefore, Japan and the UK can be considered leading nations in the implementation of the Ayano Minamihashi1. Introduction 6 Implementing Medical AI: A Comparative Study of Japan and the UK
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