The False Necessity of Scale: Intelligence, Abstraction, and the Limits of Control

Contemporary theories of intelligence, governance, and artificial intelligence alignment widely presuppose that intelligence must scale in power, abstraction, and scope in order to remain effective. Within this framing, abstraction, centralization, and corrigibility are treated as intrinsic requirements of intelligent systems operating under complexity. This paper challenges that assumption. It argues that scale, abstraction, and the need for corrigibility are not epistemic necessities of intelligence itself, but historically contingent responses to political and administrative strategies of control. Drawing on structural analysis rather than moral or ideological critique, the paper reframes abstraction as a compensatory compression mechanism for action at distance, and corrigibility as a prosthetic required once perception and action have been separated by scale. It shows that many contemporary failure modes—misalignment, loss of reality-contact, institutional drift, and moral inoperability—are better understood as consequences of treating domination-oriented scale as a design constraint rather than as properties of intelligence per se. The paper concludes by reopening a neglected question: whether the central problem of alignment lies in managing scaled intelligence more effectively, or in questioning the presumed necessity of scale itself.