Role Based Checks and Balances in Autonomous AI Teams

This paper proposes a role-based governance model for autonomous AI teams operating under client authorization. The model distinguishes three kinds of authority: proposal, decision, and action. These powers are not assigned to three fixed agents. Instead, organizational responsibilities are distributed across six roles: Chief of Staff, Communication, Planning, Operations Coordination, Recruitment, and Acceptance Review. Final decision authority remains with the client. The Chief of Staff serves as the client's secretary and coordinates the other roles without acquiring superior decision-making authority. Each functional role retains independent judgment within its assigned responsibilities and boundaries. The paper draws a limited comparison with popular sovereignty and constitutional checks and balances in the United States. The purpose of this comparison is to examine how authority can be distributed and constrained, rather than to suggest that an AI organization is equivalent to a democratic political system. The paper also outlines possible mechanisms for authorization, refusal, independent review, and accountability, together with an experimental plan for evaluating their effectiveness. This work is a conceptual proposal. No empirical evaluation is reported, and no claims of demonstrated improvements in safety, reliability, or efficiency are made. The proposed framework is intended to support further discussion, implementation, and experimental investigation.