From Algorithms to Accountability

Abstract

The incorporation of Artificial Intelligence (AI) in the healthcare sector ushered in an additional era of technical advancement impacting diagnostics, patient care, and treatment. However, it also presents significant legal and ethical concerns. The current approach has both substantial benefits and risks. Although AI delivery is more efficient and accessible, developers and users raise issues of responsibility and accountability. The primary legal and ethical dimensions of these problems include the opacity of AI algorithms, potential bias, and the complex relationship between developers, healthcare providers, and regulators. This research aims to examine the legal frameworks that govern the use of AI in healthcare. It has three main goals: researching the current legal system that supports the integration of AI into the healthcare sector, identifying gaps related to assigning accountable actors within the AI-assisted systems, and proposing strategies to tackle legal risks in AI-assisted healthcare systems. This chapter is based on doctrinal research that critically examines the existing sources of legal information, including laws, case laws, and academic work. This chapter has three main sections: data privacy, informed content, lack of transparency, ambiguity, and risks from using non-transparent AI. The results of this study show significant limitations on the current legal frameworks, particularly on the issue of developers and other supporting actors’ accountability for malfunctioning AI systems or AI bias. As a result, a final set of recommendations, including a flexible legal framework and a specialist oversight body for those mentioned above ethical and lawful issues, is generated from AI in healthcare.

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