Integrating Artificial Intelligence in Diagnostic Radiography: Implications for Accuracy, Ethics, and Professional Autonomy

Abstract

Artificial Intelligence (AI) is rapidly transforming diagnostic radiography worldwide, offering remarkable potential to enhance image interpretation accuracy, workflow efficiency, and patient outcomes [1,2]. However, in developing health systems such as Pakistan’s, AI integration introduces complex challenges surrounding ethics, accountability, and professional autonomy [3]. This study examines the implications of AI adoption in diagnostic radiography within Pakistan, focusing on three key dimensions: diagnostic accuracy, ethical considerations, and professional autonomy. Using data collected from 400 radiographers and radiologists across tertiary hospitals and imaging facilities, Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to assess the relationships among AI integration, perceived diagnostic accuracy, ethical responsibility, and autonomy. The findings indicate that AI integration significantly improves diagnostic accuracy and efficiency but raises concerns about ethical transparency, data governance, and potential erosion of radiographers’ decision-making power [4,5]. The study emphasizes the need for robust national frameworks to guide ethical AI use and safeguard professional roles in radiographic practice [6]. Policy recommendations include developing national AI integration guidelines, establishing ethical oversight bodies, and enhancing digital literacy and professional training among healthcare personnel to ensure responsible adoption of AI in Pakistan’s radiography sector.