AI changes who owns computer code and who is responsible for errors
It Is Not My Code Anymore
Software EngineeringArtificial Intelligence
Summary
When people use AI to help write computer code, it becomes unclear who actually created the code and who is responsible if it doesn’t work properly. The authors discuss why just knowing who produced a problem in the code isn’t enough to decide who should fix it or who should be in charge. They suggest that quality checks should focus on whether the service the code provides meets the needed outcome, not just on the code itself. Their ideas also apply when AI solves problems without creating traditional code, meaning responsibilities might shift but goals remain the same.
AI-assisted programmingcode ownershipsoftware responsibilityquality engineeringservice outcomeacceptance criteriacode reviewprogram generationsoftware productionauthorship
Authors
Augusto Camargo
Abstract
AI-assisted programming raises distinct questions about who produces code, who feels ownership of it, and who is responsible when it fails. This research note examines these distinctions through a hypothetical enrollment failure and a selective reading of the literature. Identifying the producer of a defective expression does not, by itself, determine the duties of reviewers, release decision-makers, or service operators. Collective ownership likewise leaves those duties to be specified. The discussion then considers how quality engineering can evaluate both generated implementations and the processes that produce them. Acceptance criteria should be justified by the required service outcome, with component checks contributing evidence toward that outcome. This perspective also permits comparison with systems that perform a task without generating a separate program for it. Such substitution would change the object of authorship while leaving the service obligation intact. The note reports no new empirical results; it proposes distinctions and evaluation questions for AI-assisted software production.