CivicTwin – Rethinking Representation in the AI Era

The future remains deeply uncertain, but the likelihood of anything resembling this scenario materialising is minimal.

We propose a decentralised system for aggregating individual ethical frameworks to address the limitations of current political systems.

This system, CivicTwin , functions as a predictive model for individual legislative preferences, built using a combination of identity verification, self-reported data, and machine-learning.

CivicTwin seeks to realign the interests of representatives with the actual needs of their constituents, ensuring that voter intent is accurately represented in parliamentary decision-making.

Users may delegate proxy votes to digital instantiations of prominent political figures, enabling these representations to vote on their behalf for specific issues.

To preserve the integrity of the voting process, a chat feature will not be included.

The successful implementation of CivicTwin relies on several critical assumptions: Public Interest , Engagement , and Trust .

The platform must garner widespread public support and confidence in both its purpose and execution.

Users will only accept AI-driven decision-making if it is transparent, explainable, and demonstrably accurate.