Socio-Ethical Implications and Public Trust in Generative AI for Early Cancer Detection: The Healthcare Sector of Pakistan

Abstract

AI has now evolved to be a revolutionary resource within the cancer field, offering insights to enhance diagnostics, customization, and workflow optimization. Nevertheless, the AI in the care of patients with cancer implies the emergence of many ethical challenges, including bias, privacy, transparency, and accountability. This paper examines these ethical concerns and provides recommendations for the effective implementation of AI in cancer treatment. Artificial intelligence has had potential as far as cancer is concerned, in diagnosis, detection, and treatment. Deep learning algorithms are being used more and more to process medical images, predict patients' results, and assist clinical decision-making. Although all this is beneficial, the moral factor is vital because of the implications of treating cancer. The risks are linked to algorithmic discrimination, data manipulation, and the lack of transparency. These ethical issues need to be understood and tackled. opportunities that might help introduce AI safely and fairly in oncology. The conclusion of the findings shows that although AI-aided diagnostic tools increase the accuracy of early detection and the assurance of clinicians, data privacy with demographic bias and the marginal utilization of bias-monitoring mechanisms are concerns and thus significant barriers to trust.

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