Federated Cognitive Parliament: A Democratic Framework for Agentic Decision-Making Over Data
Abstract
As more autonomous AI agents are deployed in the form of distributed data ecosystems, there is an increased pressure on the necessity of having transparent, responsible, and ethically consistent decisions. Classical frameworks of governance in dealing with complexity of federated and setting where stakeholders possess various requirements of privacy, compliance, utility, and security would not be viable. The paper recommends a democratic and deliberative form of government (Federated Cognitive Parliament (FCP) where sovereign agents are the digital agents which discuss, bargain and vote on the information-related move. The paper is developed on Azure AI Foundry, Semantic Kernel and Power Platform orchestration. FCP provides the opportunity of governed agreement with the help of clear rationale, argumentation history, and transparency grades. Based on the principles of multi-agent systems, deliberative democracy, and explainable AI, FCP sets up a scalable paradigm of federated data management that builds trust, decreases risk, makes sure to comply with the organizational values and regulatory demands.
