From Joint to Differentiated Liability: Reforming Ukrainian Medical Law in Light of the EU AI Act and the Estonian Experience

Abstract

Background: The growing use of high-risk artificial intelligence (AI) systems in healthcare challenges traditional models of medical liability, particularly where clinical decisions emerge from interactions among healthcare professionals, healthcare institutions, software providers, and algorithmic systems. In such circumstances, establishing causation and allocating responsibility becomes significantly more complex because of algorithmic opacity, distributed decision-making, and the involvement of multiple actors with different degrees of control over AI-related risks. Method: This study employs doctrinal and comparative legal methods to examine the transformation of liability models in the context of AI-assisted medical decision-making. The analysis is based on Ukrainian civil and medical law, Regulation (EU) 2024/1689 ‘the EU Artificial Intelligence Act’ (EU AI Act), standards of access to justice under Article 6 of the European Convention on Human Rights, and the Estonian model of digital healthcare governance and accountability. Results and Conclusions: The study demonstrates that traditional models of joint liability are increasingly inadequate for disputes involving high-risk medical AI systems because they fail to distinguish between actors exercising different degrees of control over algorithmic risk. It further demonstrates that the EU AI Act provides both a normative and conceptual foundation for a differentiated liability framework based on functional responsibility, human oversight, and risk governance. The article pays particular attention to the procedural significance of explainability, logging, and traceability as mechanisms that support causation assessment, access to evidence, and effective judicial review. The Estonian experience illustrates how digital accountability infrastructure, supported by clear institutional responsibilities and legal regulation, can strengthen oversight of AI-assisted medical decisionmaking. The article identifies key legislative gaps in Ukrainian medical law on AI-assisted healthcare. It proposes practical reform directions, including a differentiated liability model based on control over algorithmic risk. It concludes that this approach provides a more coherent and legally predictable framework for allocating responsibility in AI-assisted healthcare than traditional models of collective liability and aligns with emerging European approaches to AI governance and liability.