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AI explanations may cause over-reliance in novice users, study finds

By PulseAugur Editorial · [1 sources] ·

A new study published on arXiv explores how novice users calibrate their reliance on AI tools when making decisions without immediate performance feedback. The research indicates that AI explanations can inadvertently lead to over-reliance among users. However, higher self-reported understanding of the task is associated with more selective and appropriate reliance on AI assistance. AI

IMPACT Findings suggest a need for careful design of AI explanations to prevent over-reliance and ensure appropriate user calibration in decision-making tasks.

RANK_REASON The cluster contains a research paper published on arXiv detailing findings about human-AI interaction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI explanations may cause over-reliance in novice users, study finds

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The cluster contains a research paper published on arXiv detailing findings about human-AI interaction. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Eun Jeong Kang (Xianpi), Peter (Xianpi), Duan, Swati Mishra ·

    Novice Reliance Calibration in AI-Assisted Decision Making: The Role of Explanations and Self-Assessment

    arXiv:2610.07800v1 Announce Type: cross Abstract: Artificial Intelligence (AI) tools are widely used to support decision making in tasks and domains where no immediate performance feedback is available. In these settings, users cannot learn to adjust their reliance behavior over …

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