Generative Artificial Intelligence (GAI) Divide: An Empirical Examination of the Micro–Macro Factors that Predict GAI Knowledge and Use

Christopher Ball, Kuo‐Ting Huang
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Abstract

ABSTRACT Generative artificial intelligence (GAI), a branch of AI capable of generating new content from human input has the potential to impact every aspect of our society. However, as with any emerging technology, the benefits and detriments of GAI may not be evenly distributed, leading to digital inequality. Aspects like AI access, effectively usage, and usage outcomes could define this emerging and evolving GAI divide. To fill the current research gap on GAI inequality, this study aims to empirically explore the factors that may contribute to a GAI divide to ensure that the benefits of this technology are distributed equitably throughout society. To address these challenges, An online survey will be conducted to examine both macro‐ and micro‐level factors that may potentially proliferate and ameliorate the GAI divide.
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生成式人工智能(GAI)划分:预测GAI知识和使用的微观-宏观因素的实证检验
生成式人工智能(GAI)是人工智能的一个分支,能够从人类输入中生成新的内容,它有可能影响我们社会的方方面面。然而,与任何新兴技术一样,GAI的利与弊可能不会平均分配,从而导致数字不平等。AI访问、有效使用和使用结果等方面可以定义这种新兴和不断发展的GAI鸿沟。为了填补目前对GAI不平等的研究空白,本研究旨在实证探索可能导致GAI鸿沟的因素,以确保这项技术的利益在整个社会中公平分配。为了应对这些挑战,将进行一项在线调查,以检查可能扩大和改善GAI鸿沟的宏观和微观因素。
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来源期刊
Proceedings of the Association for Information Science and Technology
Proceedings of the Association for Information Science and Technology Social Sciences-Library and Information Sciences
CiteScore
1.30
自引率
0.00%
发文量
164
期刊介绍: Information not localized
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