Balancing AI Innovation and Data Privacy in Oracle Cloud-Based Health Systems
Authors: Gopi Krishna Kalpinagarajarao
DOI: https://doi.org/10.5281/zenodo.14785713
Short DOI: https://doi.org/g83swx
Country: USA
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Abstract: Artificial Intelligence (AI) technologies are transforming the healthcare industry through major innovations in patient care, operational efficiency and decision-making. As a strong platform to integrate AI-driven solutions into health systems, Oracle Cloud Infrastructure (OCI) provides scalability in computing power, advanced analytics, and comprehensive data management. Though healthcare hugely benefits from these advances in AI, data security, privacy, and compliance are other sides of the coin, particularly given stringent legislation such as GDPR, HIPAA, and regional health data protection laws. This paper investigates how AI innovation and data privacy interrelate inside Oracle cloud health systems. It considers approaches to avoid falling into a situation where the use of AI for predictive analytics, diagnostics, and personalized medicine can be exploited at the expense of maintaining ethical use of health data. It will focus on key areas like Oracle Security Frameworks, Advanced Encryption Methods, Data anonymization techniques and Compliance mechanisms. The paper also names challenges in removing bias at the level of the AI algorithms, maintaining transparency, and building stakeholders' trust in AI algorithms. The discussion centers around the need to develop AI solutions that are both technically robust and in keeping with privacy-centric principles through case studies and industry insights. To contribute to working out a sustainable and ethically workable integrated AI into Oracle-type health systems, this research takes a holistic approach by working out the implications of the integration, considering data privacy implications.
Keywords: Artificial Intelligence (AI), Oracle Cloud Infrastructure (OCI), Healthcare Systems, Data Privacy, GDPR, HIPAA, Data Security, Predictive Analytics
Paper Id: 232087
Published On: 2025-01-07
Published In: Volume 13, Issue 1, January-February 2025