When Visibility Outpaces Verification: Delayed Verification and Narrative Lock-in in Agentic AI Discourse

TL;DR

This study examines how social proof and delayed verification in online discussions about agentic AI can lead to early, unverified narratives becoming dominant, impacting trust and safety.

Contribution

It introduces a novel analysis of verification timing and social proof effects in online AI discourse, highlighting the 'Popularity Paradox' and proposing interventions for safer AI communication.

Findings

High-visibility discussions show delayed or no verification cues.

Early unverified claims tend to become dominant narratives.

Delayed verification creates a window for cognitive biases.

Abstract

Agentic AI systems-autonomous entities capable of independent planning and execution-reshape the landscape of human-AI trust. Long before direct system exposure, user expectations are mediated through high-stakes public discourse on social platforms. However, platform-mediated engagement signals (e.g., upvotes) may inadvertently function as a ``credibility proxy,'' potentially stifling critical evaluation. This paper investigates the interplay between social proof and verification timing in online discussions of agentic AI. Analyzing a longitudinal dataset from two distinct Reddit communities with contrasting interaction cultures-r/OpenClaw and r/Moltbook-we operationalize verification cues via reproducible lexical rules and model the ``time-to-first-verification'' using a right-censored survival analysis framework. Our findings reveal a systemic ``Popularity Paradox'': high-visibility discussions in both subreddits experience significantly delayed or entirely absent verification cues compared to low-visibility threads. This temporal lag creates a critical window for ``Narrative Lock-in,'' where early, unverified claims crystallize into collective cognitive biases before evidence-seeking behaviors emerge. We discuss the implications of this ``credibility-by-visibility'' effect for AI safety and propose ``epistemic friction'' as a design intervention to rebalance engagement-driven platforms.