Developing Ethical AI Models in Healthcare: A U.S. Legal and Compliance Perspective on HIPAA and CCPA
Abstract
The integration of artificial intelligence (AI) into healthcare offers transformative potential for improving patient outcomes, enhancing operational efficiency, and advancing medical research. However, the adoption of AI in healthcare also introduces significant ethical and legal challenges, particularly in ensuring compliance with the Health Insurance Portability and Accountability Act (HIPAA) and the California Consumer Privacy Act (CCPA). This paper examines the legal and ethical considerations associated with AI in healthcare, emphasizing the importance of transparency, accountability, and privacy. It analyzes the requirements of HIPAA and CCPA, explores the ethical dilemmas posed by AI decision-making, and identifies gaps in existing frameworks. A conceptual model for ethical AI in healthcare is proposed, incorporating data governance principles, algorithmic integrity, and stakeholder collaboration. Case studies of successful AI applications in healthcare highlight best practices, challenges, and lessons learned, offering practical insights for implementing ethical AI systems. The paper concludes with recommendations for developers, regulators, and healthcare providers to foster compliance, equity, and ethical AI integration. Future research directions, including global perspectives and emerging technologies, are also discussed, providing a comprehensive roadmap for advancing ethical AI in healthcare.
Keywords
Ethical AI
Healthcare compliance
HIPAA
CCPA
Data privacy
Algorithmic
accountability
References
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