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The integration of artificial intelligence (AI) into palliative care offers the possibility of improved patient outcomes through enhanced decision-making, personalized care, and reduced healthcare provider burden. However, the use of AI in this sensitive area presents significant ethical challenges which require serious consideration to ensure that technology serves the best interests of patients without compromising their rights or well-being. This narrative review explores the key ethical issues associated with AI in palliative care, with a focus on low-resource settings where these challenges are often intensified. The review examines essential ethical principles such as autonomy, beneficence, non-maleficence, and justice, and identifies critical concerns including data privacy, informed consent, algorithmic bias, and the risk of depersonalizing care. It also highlights the unique difficulties faced in low-resource environments, where the lack of infrastructure and regulatory frameworks can exacerbate these ethical risks. To address these challenges, the review offers actionable recommendations, such as developing context-specific guidelines, promoting transparency and accountability through explainable AI (XAI), and conducting regular ethical audits. Interdisciplinary collaboration is emphasized to ensure that AI systems are ethically designed and implemented, respecting cultural contexts and upholding patient dignity. This study contributes to the ongoing discourse on ethical AI integration in healthcare, indicating the need for careful consideration of ethical principles to ensure that AI enhances rather than undermines the compassionate care at the heart of palliative care. These findings serve as a foundation for future research and policy development in this emerging field. • Ethical integration of AI in palliative care requires addressing critical issues like informed consent, data privacy, algorithmic bias. • The paper emphasizes the unique challenges faced in low-resource settings, such as limited infrastructure and inequitable access to AI technologies. • Recommendations include promoting transparency through explainable AI (XAI), conducting regular ethical audits, and developing culturally sensitive guidelines. • AI has the potential to enhance palliative care delivery, but its implementation must prioritize patient dignity and equitable access.
Adegbesan et al. (Tue,) studied this question.