1. I favor the interdisciplinary collaboration among a diverse team of experts and continuous education of users is important to improve the safety of medical AI systems. All of the stakeholders like clinicians, data scientists, and patient representatives can work together as clinicians can understand the rationale behind AI decisions, data scientists can train with diverse data sets with more understanding of clinical settings to reduce the risk of biased outcomes, and the patient’s perspective can also consider which is crucial for the trust and verification. This collaborative approach ensures that different viewpoints are considered where ethical consideration is vital.
2. In my opinion, transparency is the main key characteristic that can build trust and confidence in medical AI systems, where AI decisions and processes are clear and understandable to clinicians. To ensure relevance and practicality, incorporating clinical expertise during the development and deployment stages will be also crucial. This also has to ensure high standards of data privacy and security to protect patient information and adhering to regulatory standards can also establish trust in the system use within the community.