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This paper analyzes the Terms of Service (ToS) of popular AI coding assistants to understand how accountability is allocated between tool providers and developers. The analysis reveals a consistent trend of shifting responsibility for code correctness, safety, and legal compliance onto users, despite increasing agent autonomy. Based on these findings, the paper proposes a research roadmap for developing accountable agents in software engineering, focusing on modeling responsibility, designing governance artifacts, and developing supporting tooling.
AI coding assistants' Terms of Service overwhelmingly place responsibility for code correctness, safety, and legal compliance on the user, creating a potential accountability gap as these tools become more autonomous.
AI coding assistants and autonomous agents are becoming integral to software development workflows, reshaping how code is produced, reviewed, and maintained. While recent research has focused mainly on the capabilities and impacts of productivity of these systems, much less attention has been paid to accountability: who is responsible when agents generate, modify, or recommend code? In practice, accountability is defined through the Terms of Service (ToS) and related policy documents that govern the use of AI-powered development tools. In this vision paper, we present a comparative analysis of the Terms of Service for widely used AI coding assistants and agent-enabled development tools. We examine how these documents allocate ownership, responsibility, liability, and disclosure obligations between tool providers and software developers, and we identify common patterns and divergences between providers. Our analysis reveals a consistent tendency to shift responsibility for correctness, safety, and legal compliance onto users, as well as substantial variation in how providers address issues such as indemnification, data reuse, and acceptable use. Based on these findings, we argue that existing policy frameworks are poorly aligned with increasingly agent-mediated and autonomous software development workflows. We outline a research roadmap for accountable agents in software engineering, identifying challenges and opportunities for modeling responsibility, designing governance artifacts, developing tooling that supports accountability, and conducting empirical studies of developers'perceptions and practices.
