Evaluating the Impact of Transparency and Accountability Measures on the Ethical Implementation of Artificial Intelligence Applications in Healthcare

Abstract

This paper investigates the critical role of transparency and accountability measures in the ethical implementation of Artificial Intelligence (AI) applications within the healthcare sector. The rapid integration of AI technologies in healthcare settings has brought forth significant improvements in patient care, diagnosis, treatment planning, and healthcare management. However, this integration also poses ethical challenges, particularly regarding patient privacy, data security, and decision-making processes. We argue that enhancing transparency and accountability in AI applications can mitigate these ethical concerns, thereby fostering trust among healthcare providers, patients, and other stakeholders. Through a systematic analysis of existing literature and case studies, this research identifies key transparency and accountability measures, such as open algorithms, data protection policies, ethical audits, and stakeholder engagement strategies, and evaluates their impact on the ethical deployment of AI in healthcare. Our findings suggest that comprehensive transparency and accountability frameworks can lead to more equitable, fair, and ethical AI applications, ultimately enhancing healthcare outcomes and patient satisfaction.

Indexing terms: Ethical Implementation, Artificial Intelligence, Healthcare, Transparency, Accountability