Integrating artificial intelligence into nephrology: an exploration of ethical dilemmas in privacy, bias, and equitable access

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Integrating artificial intelligence into nephrology: an exploration of ethical dilemmas in privacy, bias, and equitable access

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Co-author 1

Intissar Haddiya intissarhaddiya@yahoo.fr Faculty of Medicine and Pharmacy of Oujda, University Mohammed First, Oujda, Morocco Department of Nephrology, Mohammed VI University Hospital, Faculty of Medicine and Pharmacy of Oujda, University Mohammed First, Oujda, Morocco Oujda Morocco * Faculty of Medicine and Pharmacy of Oujda, University Mohammed First, Oujda, Morocco Laboratory of Epidemiology, Clinical Research and Public Health, Faculty of Medicine and Pharmacy of Oujda, University Mohammed First, Oujda, Morocco Oujda Morocco

Co-author 2

Mohamedou El Hacen mouhamedoumed15@gmail.com Faculty of Medicine and Pharmacy of Oujda, University Mohammed First, Oujda, Morocco Faculty of Medicine and Pharmacy of Oujda, University Mohammed First, Oujda, Morocco Oujda Morocco -

Co-author 3

Sara Ramdani sara.ramdani001@gmail.com Faculty of Medicine and Pharmacy of Oujda, University Mohammed First, Oujda, Morocco Laboratory of Epidemiology, Clinical Research and Public Health, Faculty of Medicine and Pharmacy of Oujda, University Mohammed First, Oujda, Morocco Oujda Morocco -

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Introduction

The integration of artificial intelligence (AI) into clinical nephrology is reshaping diagnostic accuracy, treatment planning, and patient monitoring. However, this rapid evolution raises significant ethical concerns. In particular, issues surrounding data privacy, algorithmic bias, and equitable access to healthcare remain understudied in nephrology, especially among vulnerable populations with chronic kidney disease (CKD) or those facing social, linguistic, or geographic barriers.

Methods

Our work used a qualitative approach based on four clinical case scenarios created with GPT-4. Each case was designed to reflect real ethical situations that may occur in nephrology. The cases covered different settings, including systemic disease, kidney transplantation, rural healthcare, and multilingual communication. The ethical analysis by experts followed the main principles of biomedical ethics and was supported by recent literature on AI in healthcare.

Results

The analysis showed several recurring ethical challenges. AI systems depend on sensitive patient data, which increases the risk of privacy breaches. Biases in algorithms, especially when trained on limited or non-representative data, may cause inequalities in care for rural, minority, or linguistically diverse groups. Moreover, using AI tools without proper validation may lead to clinical errors and widen existing healthcare gaps.

Conclusion

AI has great potential to improve nephrology, but its use must remain ethically responsible. Protecting patient privacy, reducing bias, and ensuring equal access to care are essential to prevent harm and build trust. This study highlights the need for strong ethical oversight and collaboration between clinicians, data scientists, and policy-makers to make sure AI benefits all patients fairly.

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