Accountability in smart contracts and agentic AI: How to address the responsibility gap and retain meaningful human control?

Abstract This conceptual paper examines the ethical challenges of ascribing responsibility when an Agentic AI embedded within a smart contract leads to harm or an unintended and undesirable outcome. It becomes exceedingly difficult in such scenarios to definitively assign moral or legal blame to any human actor (e.g., the programmer, deployer, or user). Applying the tripartite framework (attributability, answerability, and accountability) of responsibility and developing accountability as an institutional concept, we demonstrate how this challenge can be addressed. Separating attributability, answerability, and accountability yields an asymmetry that has gone unremarked. Accountability, being constituted by practices that can be designed in advance, with our four conditions under which such design is legitimate rather than arbitrary, emerges to be the sense where the gap can be closed. We also propose the visionary human-in-the-lead (HITL*) approach to related AI governance. Practical strategies such as implementing tailored smart contract regulations, and making accountability distributed across legal and organizational structures, offer an actionable path to bridge the responsibility gap and maintain meaningful human control in the governance of smart contracts and Agentic AI.