## 3 Transformative Impact and Ethical Implications of AI in Healthcare
### Blockchain Technology in Healthcare AI  
Blockchain technology, or distributed ledger technology (DLT), has introduced a paradigm shift in AI-driven healthcare systems, revolutionizing how patient data are stored, accessed, and secured. This dynamic blockchain ecosystem is not just a static data repository but a transformative force that brings unprecedented transparency, efficiency, and reliability to healthcare data management [18]. The intrinsic features of blockchain, such as immutability, transparency, and decentralization, have been particularly transformative in healthcare, where the accuracy and confidentiality of patient data are of utmost importance. The secure storage of patient records, the tracking of medication supply chains, and the management of consent for data sharing are all bolstered by blockchain's tamper-proof nature, which has significant implications for patient care and privacy. These capabilities are instrumental in reducing errors, preventing fraud, and enhancing the trustworthiness of digital healthcare systems [33]. However, integrating blockchain technology in healthcare AI presents complex interactions with data protection laws such as the European Union's General Data Protection Regulation (GDPR). GDPR imposes stringent requirements on personal data processing, focusing on principles such as consent, the right to access, rectification, and the right to be forgotten. The immutable nature of blockchain creates a unique set of challenges when juxtaposed with GDPR's emphasis on data subjects' rights, necessitating a careful analysis of how blockchain's architectural features and operational mechanisms align with or diverge from GDPR principles [32]. Blockchain is not a monolithic technology but a class of technology with various forms of distributed databases, each having distinct technical and governance arrangements. This diversity means that blockchain compatibility with GDPR cannot be generalized; it must be evaluated on a case-by-case basis, considering each blockchain use case's specific technical design and governance setup. This nuanced understanding is vital in healthcare AI, where patient data security and privacy are critical. While blockchain's core features offer significant advantages for managing healthcare data, their compatibility with GDPR principles needs careful examination. For instance, GDPR emphasizes the rights of data subjects, including the right to access, rectification, and erasure ('right to be forgotten'). However, the blockchain's immutable nature poses challenges to these rights, as data modification or removal is difficult once added to the blockchain, conflicting with GDPR's requirements. Private and permissioned blockchains might be more readily designed to comply with GDPR than public and permissionless networks in healthcare AI, where data sensitivity is high. In a permissioned blockchain, participants are known and can establish contractual relationships, which facilitates compliance with GDPR's requirements for data processing and protection. Several considerations must be considered to align blockchain applications in healthcare AI with GDPR. Data Protection by Design is a principle that should be incorporated into the blockchain's architecture from the outset, ensuring that data protection is an integral part of the system. Selective Data Recording can be explored to record only essential data on the blockchain, aligning with the GDPR's data minimization principle. Consent management must be robust, especially for sensitive health data. Interoperability with existing systems is crucial to ensuring blockchain solutions can interact seamlessly with existing healthcare data systems, which might be subject to different data protection regulations. Lastly, innovative solutions for data erasure, such as advanced encryption or off-chain storage, must be investigated to address the challenges posed by blockchain's immutability to the GDPR's right to erasure [32].