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AI-driven wellness initiatives raise important ethical issues and obstacles, especially related to data privacy, algorithmic bias, and transparency. Although these programs present possible advantages, such as tailored insights and better healthcare access, they also raise issues regarding the responsible handling of sensitive information, the risk of biased suggestions, and the necessity for clarity in AI-driven decisions. The transformation and enhancement of long-term care systems and health results face notable obstacles within existing healthcare regulations. Recent technological progress has sparked interest in innovative healthcare applications, making this sector a burgeoning area for research. AI-based monitoring and decision support systems appear to have potential in expanding personalized care programs to remote and home environments (Thompson et al. in J Bus Res 124:676–683, 2021). The World Health Organization (WHO) acknowledges the essential function of technology in effectively incorporating long-term healthcare services into the daily routines of patients. Technology is deemed essential for attaining universal health coverage across all age groups by facilitating efficient integration and service delivery. Technological innovations, especially in AI and robotics, are currently utilized to aid healthcare research and practice. In the last ten years, the exploration of the use of AI to improve essential clinical processes and results has consistently increased. Decision support systems powered by AI can enhance clinical workflows, increase patient safety, assist in diagnosis, and facilitate personalized treatment. Numerous digital technologies, such as intelligent mobile and wearable devices, have been created to collect data and analyse information for evaluating health and monitoring personalized treatment advancements. Furthermore, social and physical support systems are being implemented to assist people in their rehabilitation from disease, injury, or sensory, motor, and cognitive disabilities. Data protection aims to safeguard personal information against unauthorized access by third parties, malicious threats, and misuse. It is designed to safeguard personal information through various methods and techniques to maintain data confidentiality (Eden et al. in Magna Sci Adv Res Rev 10:006–013, 2024).

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Ethical Considerations and Challenges

  • 章节

  • 发表日期：

    2026年

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  • Soumi Majumder,
  • Nilanjan Dey

摘要

AI-driven wellness initiatives raise important ethical issues and obstacles, especially related to data privacy, algorithmic bias, and transparency. Although these programs present possible advantages, such as tailored insights and better healthcare access, they also raise issues regarding the responsible handling of sensitive information, the risk of biased suggestions, and the necessity for clarity in AI-driven decisions. The transformation and enhancement of long-term care systems and health results face notable obstacles within existing healthcare regulations. Recent technological progress has sparked interest in innovative healthcare applications, making this sector a burgeoning area for research. AI-based monitoring and decision support systems appear to have potential in expanding personalized care programs to remote and home environments (Thompson et al. in J Bus Res 124:676–683, 2021). The World Health Organization (WHO) acknowledges the essential function of technology in effectively incorporating long-term healthcare services into the daily routines of patients. Technology is deemed essential for attaining universal health coverage across all age groups by facilitating efficient integration and service delivery. Technological innovations, especially in AI and robotics, are currently utilized to aid healthcare research and practice. In the last ten years, the exploration of the use of AI to improve essential clinical processes and results has consistently increased. Decision support systems powered by AI can enhance clinical workflows, increase patient safety, assist in diagnosis, and facilitate personalized treatment. Numerous digital technologies, such as intelligent mobile and wearable devices, have been created to collect data and analyse information for evaluating health and monitoring personalized treatment advancements. Furthermore, social and physical support systems are being implemented to assist people in their rehabilitation from disease, injury, or sensory, motor, and cognitive disabilities. Data protection aims to safeguard personal information against unauthorized access by third parties, malicious threats, and misuse. It is designed to safeguard personal information through various methods and techniques to maintain data confidentiality (Eden et al. in Magna Sci Adv Res Rev 10:006–013, 2024).