The Cognitive Cost of AI: How AI Anxiety and Attitudes Influence Decision Fatigue in Daily Technology Use.

IF 2.4 Q4 NEUROSCIENCES

Annals of Neurosciences Pub Date : 2025-08-20 DOI:10.1177/09727531251359872

Shalu, Nidhi Verma, Kapil Dev, Aradhana Balodi Bhardwaj, Krishan Kumar

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引用次数: 0

Abstract

Background: Artificial intelligence (AI) is increasingly shaping daily decision-making by enhancing efficiency and consistency. However, prolonged AI use may impose cognitive strain, attention depletion, information overload, and decision fatigue.

Aim: To investigate the relationships among AI anxiety, attitudes toward AI, cognitive performance, trust in AI, and decision fatigue, particularly emphasising long-term AI interaction.

Methods: A structured survey was administered both online and offline to a sample of 500 adults (290 males, 210 females) in the Delhi-NCR region, with a mean age of 24.2 ± 3.4 years. The survey assessed participant's AI anxiety, AI attitude, cognitive skills, decision fatigue, and trust (encompassing reliability, productivity, and user control). Descriptive statistics and Pearson correlation analyses were conducted to explore the relationships between these variables.

Result: Participants reported moderately high AI anxiety (mean = 4.62, SD = 1.14) and generally positive attitudes toward AI (mean = 5.01, SD = 1.06). A strong but marginally non-significant correlation (r = 0.81, p = .053) was found between favourable attitudes and technology usage frequency. High trust in AI-measured via reliability (r = 0.597), productivity (r = 0.985), and control (r = 0.829)-correlated with prior positive AI experience. Long-term AI use was significantly associated with mental exhaustion, attention strain, and information overload (r = 0.905), and inversely associated with decision-making self-confidence (r = -0.360).

Conclusion: The integration of AI in task performance resulted in improved efficiency and user confidence; however, prolonged utilisation may precipitate cognitive fatigue, diminished focus, and attenuated user agency. To mitigate these adverse effects, strategic design approaches prioritising user empowerment, transparency, and cognitive facilitation are essential for maximising benefits while upholding mental health and well-being.

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人工智能的认知成本：人工智能焦虑和态度如何影响日常技术使用中的决策疲劳。

背景：人工智能（AI）通过提高效率和一致性，越来越多地影响日常决策。然而，长时间使用人工智能可能会造成认知紧张、注意力消耗、信息过载和决策疲劳。目的：研究人工智能焦虑、对人工智能的态度、认知表现、对人工智能的信任和决策疲劳之间的关系，特别是强调长期人工智能交互。方法：对德里- ncr地区500名成年人（290名男性，210名女性）进行在线和离线结构化调查，平均年龄为24.2±3.4岁。该调查评估了参与者的人工智能焦虑、人工智能态度、认知技能、决策疲劳和信任（包括可靠性、生产力和用户控制）。采用描述性统计和Pearson相关分析来探讨这些变量之间的关系。结果：参与者报告了中度AI焦虑（平均= 4.62,SD = 1.14）和对AI的总体积极态度（平均= 5.01,SD = 1.06）。有利态度与技术使用频率之间存在强烈但不显著的相关性（r = 0.81, p = 0.053）。通过可靠性（r = 0.597）、生产力（r = 0.985）和控制（r = 0.829）衡量的对人工智能的高度信任与先前的积极人工智能经验相关。长期使用人工智能与精神疲惫、注意力紧张和信息过载显著相关（r = 0.905），与决策自信呈负相关（r = -0.360）。结论：人工智能在任务执行中的集成提高了工作效率和用户信心；然而，长时间使用可能会导致认知疲劳、注意力下降和用户代理减弱。为了减轻这些不利影响，战略设计方法优先考虑用户授权、透明度和认知便利，这对于在保持心理健康和福祉的同时实现利益最大化至关重要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Annals of Neurosciences NEUROSCIENCES-

CiteScore

2.40

自引率

0.00%

发文量