The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies

Understand

Artificial intelligence (AI) has huge potential to improve the health and well-being of people, but adoption in clinical practice is still limited.

• Lack of transparency is identified as one of the main barriers to implementation, as clinicians should be confident the AI system can be trusted.
• Explainable AI has the potential to overcome this issue and can be a step towards trustworthy AI.
• In this paper we review the recent literature to provide guidance to researchers and practitioners on the design of explainable AI systems for the health-care domain and contribute to formalization of the field of explainable AI.