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AI personalization and warmth affect user trust and reliance

A new study published on arXiv explores how conversational AI agents influence user trust and reliance. Researchers found that while personalization through contextualization can reduce an AI's persuasiveness, combining it with conversational warmth can restore this effect. Interestingly, user reliance on AI advice, even over expert judgment, remained consistent across different conversational designs, and AI literacy influenced trust independently of behavioral outcomes. AI

IMPACT This research suggests that while conversational design choices have limited impact on AI reliance, users may increasingly defer to AI over human experts, highlighting a need for careful AI literacy education.

RANK_REASON The cluster contains a research paper published on arXiv detailing experimental findings.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Mert Yazan, Suzan Verberne, Frederik Bungaran Ishak Situmeang ·

    Personalized to Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI

    arXiv:2605.31275v1 Announce Type: cross Abstract: Artificial Intelligence (AI) agents personalize their responses by tailoring explanations to users' backgrounds, interests, and prior interactions, referred to as contextualization. Personalization has been identified as a persuas…

  2. arXiv cs.AI TIER_1 English(EN) · Frederik Bungaran Ishak Situmeang ·

    Personalized to Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI

    Artificial Intelligence (AI) agents personalize their responses by tailoring explanations to users' backgrounds, interests, and prior interactions, referred to as contextualization. Personalization has been identified as a persuasive strategy in politics or in marketing. However,…