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

Na Jiang (School of Management, University of Science and Technology of China, Hefei, China) (College of Business, City University of Hong Kong, Hong Kong, China)
Xiaohui Liu (Business School, University of Shanghai for Science and Technology, Shanghai, China)
Hefu Liu (School of Management, University of Science and Technology of China, Hefei, China)
Eric Tze Kuan Lim (School of Information Systems, Technology and Management, University of New South Wales, Sydney, Australia)
Chee-Wee Tan (Department of Digitalization, Copenhagen Business School, Copenhagen, Denmark)
Jibao Gu (School of Management, University of Science and Technology of China, Hefei, China)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 9 December 2022

147

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.

Keywords

Citation

Jiang, N., Liu, X., Liu, H., Lim, E.T.K., Tan, C.-W. and Gu, J. (2022), "Beyond AI-powered context-aware services: the role of human–AI collaboration", Industrial Management & Data Systems, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IMDS-03-2022-0152

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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