生成语法
多样性(控制论)
计算机科学
生成模型
知识管理
纪律
人工智能
数据科学
社会学
社会科学
作者
Keng‐Boon Ooi,Garry Wei‐Han Tan,Mostafa Al‐Emran,Mohammed A. Al‐Sharafi,Alexandru Căpățînă,Amrita Chakraborty,Yogesh K. Dwivedi,Tzu-Ling Huang,Arpan Kumar Kar,Voon‐Hsien Lee,Xiu-Ming Loh,Adrian Micu,Patrick Mikalef,Emmanuel Mogaji,Neeraj Pandey,Ramakrishnan Raman,Nripendra P. Rana,Prianka Sarker,Anshuman Sharma,Ching‐I Teng
标识
DOI:10.1080/08874417.2023.2261010
摘要
ABSTRACTIn a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. This is because of its potential to cause drastic and widespread shifts in many aspects of life that are comparable to those of the Internet and smartphones. More specifically, generative AI utilizes machine learning, neural networks, and other techniques to generate new content (e.g. text, images, music) by analyzing patterns and information from the training data. This has enabled generative AI to have a wide range of applications, from creating personalized content to improving business operations. Despite its many benefits, there are also significant concerns about the negative implications of generative AI. In view of this, the current article brings together experts in a variety of fields to expound and provide multi-disciplinary insights on the opportunities, challenges, and research agendas of generative AI in specific industries (i.e. marketing, healthcare, human resource, education, banking, retailing, the workplace, manufacturing, and sustainable IT management).KEYWORDS: Generative artificial intelligencemachine learninglarge language modelChatGPTBard Disclosure statementNo potential conflict of interest was reported by the author(s).
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