Data Privacy and Ethical Challenges in AI-Driven Cancer Care

The integration of artificial intelligence (AI) in oncology has transformed cancer care by offering personalized treatment pathways, improved diagnostics, and advanced predictive modelling. However, these advancements come with significant data privacy and ethical challenges, which must be addressed to ensure patient trust, regulatory compliance, and the equitable application of AI-driven solutions. This chapter examines the core privacy issues associated with handling sensitive patient data, including genomic, clinical, and personal information. It explores ethical frameworks guiding AI in healthcare, emphasizing principles such as autonomy, beneficence, and justice, and highlights the complexities of informed consent and data ownership in an AI-driven landscape. The chapter also addresses technical strategies for data protection, such as anonymization, federated learning, and blockchain, and assesses their effectiveness and limitations in preserving patient confidentiality. Furthermore, it considered the risks of bias inherent in cancer data and AI models, illustrating how such biases can lead to unfair outcomes and compromised patient safety. Important legal and regulatory issues were covered, including those raised by the GDPR and HIPAA, as well as compliance obstacles that may prevent the use of AI tools in international cancer procedures. By addressing the ethical conflicts between proprietary AI models and the requirements for openness in healthcare, this chapter promotes explainability and transparency in AI systems intended to build trust between patients and doctors. It concludes by outlining the future course of privacy-centric AI models and suggesting the morally sound and privacy-conscious advancements necessary for the appropriate application of AI in cancer treatment. To support the development of reliable, patient-centered AI in oncology, this chapter attempts to provide a thorough review of the ethical and data privacy situation.