Governments Should Mandate Tiered Anonymity on Social-Media Platforms to Counter Deepfakes and LLM-Driven Mass Misinformation

David Khachaturov, Roxanne Schnyder, Robert D. Mullins

Keywords: Online Content Governance, Tiered Anonymity and Identity Verification, Generative-AI Misinformation, Deepfakes, LLMs, Social-Media Regulation and Policy, Community-Based Moderation, Democratic Resilience and Information Integrity, Computational Law and AI Ethics, Platform Accountability Mechanisms

TL;DR: Paper urges governments to curb AI-driven misinformation by requiring social platforms to adopt a three-tier anonymity model, scaling ID checks and pre-publication fact-checks with account reach while safeguarding ordinary users’ privacy.

Abstract:

This position paper argues that governments should mandate a three-tier anonymity framework on social-media platforms as a reactionary measure prompted by the ease-of-production of deepfakes and large-language-model-driven misinformation. The tiers are determined by a given user's $\textit{reach score}$: Tier 1 permits full pseudonymity for smaller accounts, preserving everyday privacy; Tier 2 requires private legal-identity linkage for accounts with some influence, reinstating real-world accountability at moderate reach; Tier 3 would require per-post, independent, ML-assisted fact-checking, review for accounts that would traditionally be classed as sources-of-mass-information.

An analysis of Reddit shows volunteer moderators converging on comparable gates -- karma thresholds, approval queues, and identity proofs -- as audience size increases, demonstrating operational feasibility and social legitimacy. Acknowledging that existing engagement incentives deter voluntary adoption, we outline a regulatory pathway that adapts existing US jurisprudence and recent EU-UK safety statutes to embed reach-proportional identity checks into existing platform tooling, thereby curbing large-scale misinformation while preserving everyday privacy.

Submission Number: 513