Generative AI-Based Telemedicine Management: An Analysis of Ethical Acceptability, Medical Governance, and Patient Social Trust
Keywords:
generative ai, telemedicine, ethical acceptability, social trust, medical governance, data privacy, clinical accountabilityAbstract
The implementation of Generative AI in telemedicine management brings transformative shifts to operational efficiency while simultaneously raising complex ethical and social challenges. This study aims to analyze the ethical acceptability, medical governance mechanisms, and implications of using generative artificial intelligence on patient social trust within the digital healthcare consultation ecosystem. The methodology employed is a descriptive qualitative approach based on a systematic literature review of recent studies. The findings indicate that the ethical acceptability of Generative AI is determined by clear transparency regarding communicator identity, data privacy protection via advanced encryption, algorithmic bias mitigation, and definitive legal accountability. Furthermore, sustaining patient social trust requires active physician supervision (human-in-the-loop), accessible services, and socioculturally sensitive therapeutic communication. This study concludes that successful digital transformation in telemedicine demands a balance among technological innovation, adaptive regulation, and enhanced AI literacy for medical personnel to safeguard patient safety and dignity.
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