Using Explainable AI (XAI) for Compliance and Trust in the Healthcare Industry

Explainable AI (XAI) is emerging as a critical tool in the healthcare industry to address the challenges of trust and compliance in the adoption of machine learning models. The FDA's new guidelines have increased the regulatory scrutiny on AI systems, treating some as medical devices, thereby necessitating transparency in their decision-making processes. XAI provides the means to understand and interpret the reasoning behind AI predictions, which is crucial for ensuring accurate diagnoses, reducing unnecessary procedures, and fostering trust among healthcare providers and patients. Despite being in its early stages, XAI offers significant potential benefits, such as enhanced diagnostic capabilities and ethical decision-making, but faces challenges due to the complexity and sensitivity of medical data. By offering insight into model predictions and enabling real-time error detection, XAI can help mitigate biases and improve the reliability of AI systems, ultimately leading to better patient care and compliance with legal and ethical standards.