The Decision No One Authored: The Answerability Gap in Generative AI

Debates over automating decisions in law, medicine, and public administration divide over what human judgment adds to the application of a rule. Both sides assume judgment’s work is to supplement rule-application — to fill the gap between an abstract rule and the particular case. This paper identifies a prior gap the framing misses. Before any rule meets any case, someone must answerably settle what a system is for and what its outputs must meet: the evaluative frame the decision turns on. I call this authorship, the answerable setting of that frame and the bringing of each output under it. Authorship is distinct from, and prior to, the relations the leading governance concepts secure. Meaningful human control and human oversight can ensure that a system tracks a human’s reasons, traces to her understanding, and remains within her capacity to override, yet leave untouched whether she authored the frame those relations operate within. The argument is analytic rather than empirical: a person can satisfy every control and oversight condition and still author none of what she accepts. Control governs her relation to the system’s operation; authorship governs her relation to the frame through which operation becomes decision. I distinguish this answerability gap from the attributive gap the responsibility-gap literature addresses, show that it is invariant under the question of machine consciousness, locate the five junctures at which authorship is exercised or dropped, and argue that, when left unaddressed, the gap compounds rather than closes.