Acceptability and accountability on Artificial Intelligence among healthcare workers in selected hospitals in Isabela

Abstract

An outright improvement in accuracy, clinical efficiency and patient-directed care has been attributed to the radical integration of Artificial Intelligence (AI) in the healthcare arena. This inquiry explored the accountability and acceptability of AI among selected hospitals in the Province of Isabela. The selected participants were assessed on ethics, potential judgments, man-over-machine roles, public confidence and dignity and inherent biases, formerly and perceived usefulness, ease of use, social influence, self-efficacy and facilitating conditions, on the latter. This study was qualitatively underpinned by the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology. Inherently, themes and subthemes were purposefully extracted from the viewpoints of the selected health workers. Thus, findings denoted that accountability is strongly linked to transparency and training, governance, regulation and ethical guidelines as it  underscore the importance of regulating human oversight while safeguarding equitable caring outcomes as algorithmic biases are addressed. Consequently, the participants recognized that AI aids in enhancing diagnostic accuracy, reduces clinical workload yielding to improved patient care in terms of Acceptability. Although trepidations were evident on data privacy, lack of trainings , unethical nuances and human-centered oversight, public confidence, on the other hand, was robustly linked to accuracy, transparency and data privacy. Hence, the study concluded that a successful AI-integration maintains a harmony among ethical principles, technological advancements and man-over-machine oversight. Recommendations are centered to dynamic trainings, proposed policy frameworks and ergonomic collaboration between healthcare professionals and AI developers.