Patients, clinicians, administrators, regulators, and AI developers each need a reason to trust medical AI, and diabetes shows what that takes. Trust requires moving beyond single deterministic outputs to clear standards for medical AI provenance and performance, with each stakeholder holding its own priorities and responsibilities.
Abstract
Artificial Intelligence (AI) has the potential to impact healthcare across multiple domains. In diabetes, a complex chronic disease affecting 600 million people globally, AI is already being used from primary care to tertiary specialist care to reduce patient and clinician burden. However, for medical AI to be widely implemented and applied specifically to diabetes, such stakeholders as patients, clinicians, healthcare administrators, regulators, and AI developers will need to establish trust in this technology.
Building trust is a balancing act depending on individual priorities of stakeholders which may not necessarily align. Both probabilistic outputs and top-choice only outputs are used in medical AI. To achieve trust in AI for diabetes care, it will be necessary to move beyond expecting only single, deterministic outputs and to establish clear standards for medical AI provenance and performance. Each stakeholder has its own priorities before it will trust medical AI, and its own responsibilities for building that trust.