The Last Vote: A Multi-Stakeholder Framework for Language Model Governance

Subramanyam Sahoo, Aditi Chhawacharia

Keywords: AI Governance, Democratic Risks, ISS Score

TL;DR: We propose a mathematical framework for democratically governing AI language models through multi-stakeholder participation, risk assessment, and phased implementation to protect democratic institutions from AI-related threats.

Abstract: As artificial intelligence systems become increasingly powerful and pervasive, democratic societies face unprecedented challenges in governing these technologies while preserving core democratic values and institutions. This paper presents a comprehensive framework to address the full spectrum of risks that AI poses to democratic societies. Our approach integrates multi-stakeholder participation, civil society engagement, and existing international governance frameworks while introducing novel mechanisms for risk assessment and institutional adaptation. We propose: (1) a seven-category democratic risk taxonomy extending beyond individual-level harms to capture systemic threats, (2) a stakeholder-adaptive Incident Severity Score (ISS) that incorporates diverse perspectives and context-dependent risk factors, and (3) a phased implementation strategy that acknowledges the complex institutional changes required for effective AI governance.

Submission Number: 57