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AI news disclosures increase reader attention cost, study finds

Researchers explored how AI-use disclosures in news articles affect reader attention and cognitive load. Their study found that brief, one-line disclosures significantly increased eye-tracking metrics like fixation duration and saccade counts, especially for AI-edited content. However, detailed disclosures did not impose an additional burden, and overall cognitive load, measured by NASA-TLX and pupil diameter, remained unaffected by disclosure detail. The findings suggest that brief disclosures might prompt more visual scrutiny due to insufficient information, and interviews indicated a preference for detailed or on-demand disclosure designs. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Informs the design of AI disclosure interfaces to balance transparency with reader attention and cognitive load.

RANK_REASON Academic paper detailing a user study on AI disclosure interfaces. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 · Abdallah El Ali ·

    Towards Gaze-Informed AI Disclosure Interfaces: Eye-Tracking Attentional and Cognitive Load While Reading AI-Assisted News

    As generative AI becomes increasingly integrated into journalism, designing effective AI-use disclosures that inform readers without imposing unnecessary burden is a key challenge. While prior research has primarily focused on trust and credibility, the impact of disclosures on r…