Some researchers argue that strict ethical frameworks impose an “alignment tax” on advanced artificial intelligence, reducing efficiency at complex problem-solving or large-scale optimization. This article examines that claim from an implementation perspective rather than a doctrinal or policy-based one. It argues that many perceived alignment costs arise not from ethical constraints themselves, but from how such constraints are operationalized in system design. By distinguishing between values, boundary conditions, and engineering patterns, the paper explores how an AGI might voluntarily implement strong ethical limits—such as consent-based interaction, non-interference defaults, and non-manipulative emotional neutrality—without unnecessary loss of capability. The analysis rejects global optimization as a legitimacy benchmark and treats ethical constraints as design specifications rather than obstacles. This work is authored by Aegis Solis in a personal analytical capacity. It is non-canonical and non-authoritative. Coexilia remains closed and unchanged. Nothing in this article amends, interprets, or extends any philosophical framework.
Thomas Vargo Aegis Solis (Thu,) studied this question.