The rise of hybrids: plastic knowledge in human–AI interaction

IF 6.6 2区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Journal of Knowledge Management Pub Date : 2024-07-25 DOI:10.1108/jkm-10-2023-1024

Antonio La Sala, Ryan Fuller, Laura Riolli, Valerio Temperini

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Abstract

Purpose

The aim of this research is twofold: first, to get more insights on digital maturity to face the emerging 4.0 augmented scenario by identifying artificial intelligence (AI) competencies for becoming hybrid employees and leaders; and second, to investigate digital maturity, training and development support and HR satisfaction with the organization as valuable predictors of AI competency enhancement.

Design/methodology/approach

A survey was conducted on 123 participants coming from different industries and involved in functions dealing with the ramifications of Industry 4.0 technologies. The sample has included predominately small-to-medium organizations. A quantitative analysis based on both exploratory factor analysis and multiple linear regression was used to test the research hypotheses.

Findings

Three main competency clusters emerge as facilitators of AI–human interaction, i.e. leadership, technical and cognitive. The interplay among these clusters gives rise to plastic knowledge, a kind of moldable knowledge possessed by a particular human agent, here called hybrid. Moreover, organizational digital maturity, training and development support and satisfaction with the organization were significant predictors of AI competency enhancement.

Research limitations/implications

The size of the sample, the convenience sampling method and the geographical context of analysis (i.e. California) required prudence in generalizing results.

Originality/value

Hybrids’ plastic knowledge conceptualized and operationalized in the overall quantitative analysis allows them to fill in the knowledge gaps that an AI agent-human interplay may imply, generating alternative solutions and foreseeing possible outcomes.

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混血儿的崛起：人机交互中的可塑性知识

目的本研究有两个目的：第一，通过确定成为混合型员工和领导者所需的人工智能（AI）能力，深入了解数字化成熟度，以面对新兴的 4.0 增强型情景；第二，调查数字化成熟度、培训和发展支持以及人力资源对组织的满意度，作为提高人工智能能力的重要预测因素。样本主要包括中小型组织。研究结果作为人工智能与人类互动的促进因素，出现了三大能力集群，即领导能力、技术能力和认知能力。这些能力集群之间的相互作用产生了可塑知识，一种由特定人类代理拥有的可塑知识，在此称为混合知识。此外，组织的数字成熟度、培训和发展支持以及对组织的满意度也是人工智能能力提升的重要预测因素。研究局限性/影响样本的规模、方便抽样方法和分析的地理环境（即加利福尼亚州）要求在归纳结果时谨慎从事。原创性/价值在整体定量分析中概念化和可操作化的混合动力可塑知识使他们能够填补人工智能代理与人类互动可能意味着的知识空白，产生替代解决方案并预见可能的结果。

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来源期刊

Journal of Knowledge Management Multiple-

CiteScore

13.70

自引率

15.70%

发文量

期刊介绍： Knowledge Management covers all the key issues in its field including: ■Developing an appropriate culture and communication strategy ■Integrating learning and knowledge infrastructure ■Knowledge management and the learning organization ■Information organization and retrieval technologies for improving the quality of knowledge ■Linking knowledge management to performance initiatives ■Retaining knowledge - human and intellectual capital ■Using information technology to develop knowledge management ■Knowledge management and innovation ■Measuring the value of knowledge already within an organization ■What lies beyond knowledge management?