{"title":"The academic industry’s response to generative artificial intelligence: An institutional analysis of large language models","authors":"Nir Kshetri","doi":"10.1016/j.telpol.2024.102760","DOIUrl":null,"url":null,"abstract":"<div><p>This paper examines academic institutions' heterogeneous initial responses to generative AI (GAI) tools like ChatGPT and factors influencing increased acceptance over time. GAI's disruptive nature coupled with uncertainty about impacts poses adoption challenges. However, external pressures from stakeholders seeking GAI integration contribute to changing attitudes. Actions of institutional change agents also drive growing acceptance by increasing awareness of GAI advantages. They challenge prevailing logics emphasizing assessments, proposing new values around employability and job performance. Additionally, academic institutions reevaluating GAI's value creation potential through applications and evolving business models contributes to favorable responses. The paper proposes an institutional theory framework explaining dynamics underpinning academic institutions' assimilation of GAI. It highlights how various mechanisms like external pressures, institutional entrepreneurs' theorization efforts justifying technology use, and internal sensemaking shape institutional norms and values, enabling academic systems' adaptation. The study informs policy and practice while directing future research toward validating propositions empirically and examining contextual dimensions including industry characteristics affecting GAI adoption.</p></div>","PeriodicalId":22290,"journal":{"name":"Telecommunications Policy","volume":"48 5","pages":"Article 102760"},"PeriodicalIF":5.9000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Telecommunications Policy","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0308596124000570","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 0
Abstract
This paper examines academic institutions' heterogeneous initial responses to generative AI (GAI) tools like ChatGPT and factors influencing increased acceptance over time. GAI's disruptive nature coupled with uncertainty about impacts poses adoption challenges. However, external pressures from stakeholders seeking GAI integration contribute to changing attitudes. Actions of institutional change agents also drive growing acceptance by increasing awareness of GAI advantages. They challenge prevailing logics emphasizing assessments, proposing new values around employability and job performance. Additionally, academic institutions reevaluating GAI's value creation potential through applications and evolving business models contributes to favorable responses. The paper proposes an institutional theory framework explaining dynamics underpinning academic institutions' assimilation of GAI. It highlights how various mechanisms like external pressures, institutional entrepreneurs' theorization efforts justifying technology use, and internal sensemaking shape institutional norms and values, enabling academic systems' adaptation. The study informs policy and practice while directing future research toward validating propositions empirically and examining contextual dimensions including industry characteristics affecting GAI adoption.
本文研究了学术机构对 ChatGPT 等生成式人工智能(GAI)工具的不同初始反应,以及随着时间推移影响接受度提高的因素。GAI 的破坏性和影响的不确定性给采用带来了挑战。然而,利益相关者寻求整合 GAI 的外部压力有助于改变人们的态度。机构变革推动者的行动也通过提高对全球审计与分析优势的认识,促使接受度不断提高。他们对强调评估的普遍逻辑提出挑战,围绕就业能力和工作绩效提出新的价值观。此外,学术机构通过应用和不断发展的商业模式,重新评估 GAI 的价值创造潜力,也促进了良好的反应。本文提出了一个制度理论框架,解释学术机构吸收 GAI 的动力。它强调了各种机制,如外部压力、机构创业者为证明技术使用的合理性而进行的理论化努力,以及内部感性认识如何形成机构规范和价值观,从而使学术系统得以适应。这项研究为政策和实践提供了参考,同时也引导未来的研究以实证的方式验证命题,并研究影响 GAI 采用的背景因素,包括行业特征。
期刊介绍:
Telecommunications Policy is concerned with the impact of digitalization in the economy and society. The journal is multidisciplinary, encompassing conceptual, theoretical and empirical studies, quantitative as well as qualitative. The scope includes policy, regulation, and governance; big data, artificial intelligence and data science; new and traditional sectors encompassing new media and the platform economy; management, entrepreneurship, innovation and use. Contributions may explore these topics at national, regional and international levels, including issues confronting both developed and developing countries. The papers accepted by the journal meet high standards of analytical rigor and policy relevance.