Andry Jullius
Universitas Islam Nusantara, Bandung

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Accountability for Telemedicine Algorithm Errors: A Normative Analysis of Potential Regulatory Gaps in Indonesia Andry Jullius; Ahmad Ma'mun Fikri
Jurnal Iman dan Spiritualitas Vol. 5 No. 4 (2025): Jurnal Iman dan Spiritualitas
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/jis.v5i4.58589

Abstract

The rapid development of information and communication technology has brought significant changes to the provision of healthcare services, particularly through the use of telemedicine. In Indonesia, telemedicine plays a strategic role in improving access to healthcare services in geographically dispersed areas. Along with this development, the use of artificial intelligence-based medical algorithms is increasingly widespread in the diagnosis process, clinical decision-making, and treatment recommendations. While offering efficiency and innovation, the use of these algorithms also raises new legal challenges, particularly regarding liability for algorithmic errors that can harm patient safety. This study aims to analyze legal liability for algorithmic errors in telemedicine services through a normative legal research approach, focusing on identifying potential regulatory gaps in Indonesia. The research methods used include statutory, conceptual, and case studies. The analysis was conducted on relevant laws and regulations in the fields of health, consumer protection, and personal data protection, and was supported by a doctrinal review and comparison with the legal framework for telemedicine in Malaysia. The results indicate that the Indonesian legal system does not explicitly regulate liability for medical algorithm errors, so the determination of liability still relies on general principles of health law and civil law. This regulatory gap creates legal uncertainty, particularly when errors stem from algorithm design flaws, training data bias, or system failures beyond the reasonable control of medical personnel. Therefore, this study proposes the implementation of a shared liability model between physicians, telemedicine platform providers, and algorithm developers, based on the roles and causal contributions of each party. This model is considered fairer, more proportional, and able to strengthen legal protection for patients in Indonesia's AI-based telemedicine ecosystem.