Luke F. Walton

Can a person stay fully in control of an AI-shaped decision and still fail to author it? They may hold the power to override the system, be expected and encouraged to do so, and remain answerable for the outcome after the fact, yet never exercise judgment over the evaluative frame the decision turns on, inheriting that frame rather than authoring it. This article argues that the gap this opens, rather than the question of whether AI is conscious, is where responsibility for machine-mediated action is won or lost. The system's fluency is what widens it: confident, plausible, finished-looking outputs invite a person to accept the machine's framing wholesale, and that temptation operates whether or not anything is actually home. And the temptation deepens rather than recedes as the systems improve, since a reliable track record makes deference rational and erodes the felt need to check at the very juncture where checking still matters. The claim concerns responsibility, not mind. The dominant design-facing norm, meaningful human control, can close what I call the attributive gap, securing some human to whom an outcome can be traced. It leaves open an answerability gap: the traceable party, even amid a crowd of attributable parties, never exercised the judgment over the decision's evaluative frame that separates holding someone responsible from scapegoating them. Generative and decision-support systems are especially prone to produce this second gap, because their fluency lets a person keep full capacity to intervene while authoring none of what they accept. The norm that closes it is human authorship: the answerable exercise of judgment over a decision's evaluative frame, discharged at the five junctures where that judgment is most easily skipped. These are the ends a system serves, the standards its outputs must meet, their verification, their acceptance into action, and the final form for which someone stands answerable. The contribution is this positive account, and its reframing of answerability as a relation that must be exercised rather than a position one occupies. Authorship holds independent of the machine's moral status: it is owed whether or not the system is conscious, and whether or not it is right. More fundamentally, control governs the human's relation to the system's operation; authorship governs the human's relation to the evaluative frame through which that operation becomes action. Drawing on Acemoglu and Restrepo's task framework and Acemoglu and Johnson's critique of so-so automation, I argue that the deeper danger is a so-so automation of judgment, evaluative work displaced without new tasks in which human agency is strengthened. I close with three implications and a caution for design.