Ethical and Legal Dimensions of AI in Healthcare

Abstract

The ethical aspects of AI particularly in terms such as informed consent, safety and transparency, are concerned with algorithmic fairness and biases and data privacy. This includes an informed consent, where patients must understand how AI systems will be used in their care and healthcare providers need to communicate this clearly. Safety comes first along with transparency; AI algorithms need to be tested and validated extensively before they can hit the market for patient care (to make sure they are not harming patients) as healthcare providers should understand how these algorithms take decisions. This chapter provides a high-level overview of the legislative challenges and requirements those AI technologies in healthcare need to comply with regarding legal frameworks. Because AI progresses so rapidly, in many cases, regulation is not well defined and it can be unclear where the responsibility lay when an accident takes place due to a machine learning system. This should be done in a way that they can help in advancing research and ensuring the data sharing process is Operational Technology (OT) compliant within regulation of data protection laws such as Health Insurance Portability and Accountability Act (HIPAA) (USA) and General Data Protection Regulation (GDPR) (EU). Developers are creating new and exciting AI solutions resulting in IP issues including patentability guidelines and ownership rights. This chapter highlights the need for cross-disciplinary collaboration by stakeholders policymakers, health care providers and ethicists as well as technology developers to define holistic frameworks which address these ethical and legal challenges. Putting ethical principles first and solid legal structures in place means the full potential of AI for health can be realized while also ensuring safety, equity and trust.

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