CYAIHCFeb 11

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

arXiv:2602.11412v1
Originality Incremental advance
AI Analysis

This addresses a problem for AI safety and trust by highlighting how social media dynamics can hinder critical evaluation of AI systems, though it is incremental in focusing on specific online communities.

The paper investigates how high-visibility online discussions about agentic AI experience delayed verification, leading to a 'Popularity Paradox' where unverified claims solidify into biases before evidence emerges, with findings showing significantly delayed or absent verification in high-visibility threads compared to low-visibility ones.

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.

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