Ethical Issues Associated with Artificial Intelligence in Respiratory Disease Management: A Scoping Review

Abstract

Artificial intelligence (AI) applications are increasingly integrated into the management of Respiratory conditions, including Asthma, Pneumonia, and Occupational Lung Disease. While clinical benefits are evident, Ethical concerns in domains related to Data Privacy and Confidentiality, Algorithmic bias, and Equity, Transparency and Black box pattern, Accountability, Patient autonomy, and Surveillance remain insufficiently examined. This scoping review aimed to map and synthesize published evidence that described ethical challenges associated with the deployment of AI technologies in the management of respiratory disease. A scoping review was conducted in accordance with Joanna Briggs Institute (JBI) guidelines, with structured searches conducted in Pub-med, Web of Science, and Scopus for peer-reviewed articles published between 2010 and 2025. Studies addressed the ethical implications of AI deployment in respiratory care were included, screening and data charting were performed independently by reviewers using predefined criteria. Out Of the 33 articles identified, 9 were screened, and 5 were included across respiratory conditions, Data Privacy and Confidentiality, Algorithmic bias, and Equity, Transparency and Black box pattern, Accountability, Patient autonomy and Surveillance. These ethical challenges were consistent, indicating systemic governance gaps rather than disease-specific ethical concerns. This review concluded that Artificial intelligence can enhance clinical decision making and is being utilized to diagnose respiratory conditions(Asthma, Pneumonia, and Occupational Lung Disease).But this review addressed 5 ethical issues including  Data Privacy and Confidentiality, Algorithmic bias, and Equity, Transparency and Black box pattern, Accountability, Patient autonomy and Surveillance. Thus for safe application of AI in respiratory disease management must require transparent AI systems and  strong ethical guidelines.