Quadratic Intelligence Swarm (QIS): Decentralized Governance for AI Networks

This article introduces the Quadratic Intelligence Swarm (QIS) protocol, a novel approach to governing decentralized AI networks without a central authority. QIS uses a multi-election system to define similarity templates and self-organize the network.

Details

The QIS protocol aims to solve the governance problem in decentralized AI systems. Unlike blockchain consensus mechanisms or federated learning, QIS takes a unique approach by running three separate elections to define the network's behavior. The first election elects a Pattern Curator, who is responsible for defining the similarity template - the set of variables and their ranges that determine which cases belong together. This template becomes the routing key for the entire network. For example, in the lung cancer use case, the curator defines fields like stage, histology, driver mutation, PD-L1 expression, and ECOG status as the key variables to group similar cases. The curator's decision on the similarity template is a critical one, as it shapes how the network will organize and route information. This is not a purely technical decision, but rather requires domain expertise to determine the most relevant factors for the given use case. By having a separate election to select the curator, QIS ensures that the network's core organizing principle is defined by subject matter experts rather than a central authority. This decentralized governance model is a key innovation of the QIS protocol.