{"title":"A bibliometric analysis deconstructing research on how cognitive technologies affects man-machine collaboration.","authors":"K. Breunig, Tina Alexandra Ngo Schwabe Strand","doi":"10.34190/eckm.24.2.1345","DOIUrl":null,"url":null,"abstract":"This paper addresses knowledge work challenges relating to emerging cognitive technologies. The field of research addressing artificial intelligence (AI), and related topics, is rapidly increasing. However, despite this emerging interest, the currently body of published research remains complex and unstructured. In particular, it remains to be understood how these technologies is implemented and cause changes in man-machine collaboration. To inform this issue, we conducted a bibliometric analysis of extant literature on AI and man-machine collaboration to take stock of extant published research in order to provide a foundation upon which both future theory and practice can be built. We based our analysis of an exhaustive structured literature search of published academic research in Web of Science (WoS) until 2020. Using the keywords digi* AND transform* OR artificial intelligence, 8 728 articles were identified. The bibliometric analysis enabled us first to identify 202 relevant articles published within the fields of business and management, and subsequently to further narrowing our scope to 25 core contributions using bibliometric coupling. A content analysis of these 25 articles revealed that whereas there is a lot of attention to the technological complexities related to the emerging cognitive technologies, there is to date limited empirical descriptions of the consequences for individuals, organizations or value creation of adopting these technologies. Our study identifies four important dimensions of man-machine collaboration; Knowledge worker, Organization, Market, and Society. Moreover, our findings reveal extant research is inconclusive with respect to the forces affecting these dimensions as different authors record both proactive forces and constraining forces associated with each of the four dimensions. Our contribution, as well as, the identification of a core canon of relevant research articles provides a foundation upon which future research and practice can be built by identifying core dimension and the forces acting upon them. ","PeriodicalId":107011,"journal":{"name":"European Conference on Knowledge Management","volume":"282 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Conference on Knowledge Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34190/eckm.24.2.1345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper addresses knowledge work challenges relating to emerging cognitive technologies. The field of research addressing artificial intelligence (AI), and related topics, is rapidly increasing. However, despite this emerging interest, the currently body of published research remains complex and unstructured. In particular, it remains to be understood how these technologies is implemented and cause changes in man-machine collaboration. To inform this issue, we conducted a bibliometric analysis of extant literature on AI and man-machine collaboration to take stock of extant published research in order to provide a foundation upon which both future theory and practice can be built. We based our analysis of an exhaustive structured literature search of published academic research in Web of Science (WoS) until 2020. Using the keywords digi* AND transform* OR artificial intelligence, 8 728 articles were identified. The bibliometric analysis enabled us first to identify 202 relevant articles published within the fields of business and management, and subsequently to further narrowing our scope to 25 core contributions using bibliometric coupling. A content analysis of these 25 articles revealed that whereas there is a lot of attention to the technological complexities related to the emerging cognitive technologies, there is to date limited empirical descriptions of the consequences for individuals, organizations or value creation of adopting these technologies. Our study identifies four important dimensions of man-machine collaboration; Knowledge worker, Organization, Market, and Society. Moreover, our findings reveal extant research is inconclusive with respect to the forces affecting these dimensions as different authors record both proactive forces and constraining forces associated with each of the four dimensions. Our contribution, as well as, the identification of a core canon of relevant research articles provides a foundation upon which future research and practice can be built by identifying core dimension and the forces acting upon them.
本文讨论了与新兴认知技术相关的知识工作挑战。人工智能(AI)及其相关主题的研究领域正在迅速增加。然而,尽管有这种新兴的兴趣,目前发表的研究仍然是复杂和非结构化的。特别是,这些技术是如何实现的以及如何引起人机协作中的变化还有待了解。为了说明这个问题,我们对现有的人工智能和人机协作文献进行了文献计量分析,以评估现有的已发表研究,以便为未来的理论和实践奠定基础。我们的分析基于对Web of Science (WoS)上发表的学术研究的详尽结构化文献检索,直到2020年。使用关键词digi* AND transform*或人工智能,共识别出8 728篇文章。通过文献计量分析,我们首先确定了在商业和管理领域发表的202篇相关文章,随后使用文献计量耦合将我们的范围进一步缩小到25篇核心贡献。对这25篇文章的内容分析显示,尽管对新兴认知技术相关的技术复杂性有很多关注,但迄今为止,对采用这些技术对个人、组织或价值创造的影响的经验描述有限。我们的研究确定了人机协作的四个重要维度;知识工作者、组织、市场与社会。此外,我们的研究结果表明,现有的研究对于影响这些维度的力量是不确定的,因为不同的作者记录了与四个维度中每个维度相关的主动力量和约束力量。我们的贡献,以及相关研究文章的核心经典的识别,为未来的研究和实践提供了一个基础,可以通过识别核心维度和作用于它们的力量来建立。