Beyond AI-powered context-aware services : the role of human–AI collaboration

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

1 Scopus Citations
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Author(s)

  • Xiaohui Liu
  • Hefu Liu
  • Eric Tze Kuan Lim
  • Chee-Wee Tan
  • Jibao Gu

Related Research Unit(s)

Detail(s)

Original languageEnglish
Number of pages32
Journal / PublicationIndustrial Management and Data Systems
Online published9 Dec 2022
Publication statusOnline published - 9 Dec 2022

Abstract

Purpose - Artificial intelligence (AI) has gained significant momentum in recent years. Among AI-infused systems, one prominent application is context-aware systems. Although the fusion of AI and context awareness has given birth to personalized and timely AI-powered context-aware systems, several challenges still remain. Given the “black box” nature of AI, the authors propose that human–AI collaboration is essential for AI-powered context-aware services to eliminate uncertainty and evolve. To this end, this study aims to advance a research agenda for facilitators and outcomes of human–AI collaboration in AI-powered context-aware services. Design/methodology/approach - Synthesizing the extant literature on AI and context awareness, the authors advance a theoretical framework that not only differentiates among the three phases of AI-powered context-aware services (i.e. context acquisition, context interpretation and context application) but also outlines plausible research directions for each stage. Findings - The authors delve into the role of human–AI collaboration and derive future research questions from two directions, namely, the effects of AI-powered context-aware services design on human–AI collaboration and the impact of human–AI collaboration. Originality/value - This study contributes to the extant literature by identifying knowledge gaps in human–AI collaboration for AI-powered context-aware services and putting forth research directions accordingly. In turn, their proposed framework yields actionable guidance for AI-powered context-aware service designers and practitioners.

Research Area(s)

  • Artificial intelligence, Context-aware, Human–AI collaboration

Citation Format(s)

Beyond AI-powered context-aware services: the role of human–AI collaboration. / Jiang, Na; Liu, Xiaohui; Liu, Hefu et al.
In: Industrial Management and Data Systems, 09.12.2022.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review