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Can AI artifacts influence human cognition? The effects of artificial autonomy in intelligent personal assistants

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  • Hu, Qian
  • Lu, Yaobin
  • Pan, Zhao
  • Gong, Yeming
  • Yang, Zhilin

Abstract

In the era of the Internet of Things (IoT), emerging artificial intelligence (AI) technologies provide various artificial autonomy features that allow intelligent personal assistants (IPAs) to assist users in managing the dynamically expanding applications, devices, and services in their daily lives. However, limited academic research has been done to validate empirically artificial autonomy and its downstream consequences on human behavior. This study investigates the role of artificial autonomy by dividing it into three types of autonomy in terms of task primitives, namely, sensing, thought, and action autonomy. Drawing on mind perception theory, the authors hypothesize that the two fundamental dimensions of humanlike perceptions—competence and warmth—of non-human entities could explain the mechanism between artificial autonomy and IPA usage. Our results reveal that the comparative effects of competence and warmth perception exist when artificial autonomy contributes to users' continuance usage intention. Theoretically, this study increases our understanding of AI-enabled artificial autonomy in information systems research. These findings also provide insightful suggestions for practitioners regarding AI artifacts design.

Suggested Citation

  • Hu, Qian & Lu, Yaobin & Pan, Zhao & Gong, Yeming & Yang, Zhilin, 2021. "Can AI artifacts influence human cognition? The effects of artificial autonomy in intelligent personal assistants," International Journal of Information Management, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:ininma:v:56:y:2021:i:c:s0268401220314493
    DOI: 10.1016/j.ijinfomgt.2020.102250
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    Cited by:

    1. Saenger, Christina & Kuchmaner, Christina A. & Bateman, Patrick J., 2024. "Betrayed by AI: How perceived betrayal by a virtual assistant affects consumers’ purchase intentions for recommended products," Journal of Business Research, Elsevier, vol. 185(C).
    2. Yi Sun & Shihui Li & Lingling Yu, 2022. "The dark sides of AI personal assistant: effects of service failure on user continuance intention," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 17-39, March.
    3. Janarthanan Balakrishnan & Yogesh K. Dwivedi, 2024. "Conversational commerce: entering the next stage of AI-powered digital assistants," Annals of Operations Research, Springer, vol. 333(2), pages 653-687, February.
    4. Peiyu Zhou & Yuguang Xie & Changyong Liang, 2023. "How to increase consumers’ continued use intention of artificial intelligence voice assistants? The role of anthropomorphic features," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-18, December.
    5. Kang, Weiyao & Shao, Bingjia, 2023. "The impact of voice assistants’ intelligent attributes on consumer well-being: Findings from PLS-SEM and fsQCA," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    6. Guo, Wenshan & Luo, Qiangqiang, 2023. "Investigating the impact of intelligent personal assistants on the purchase intentions of Generation Z consumers: The moderating role of brand credibility," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    7. Anshul Ujlayan & Sanjay Bhattacharya & Sonakshi, 2023. "A Machine Learning-Based AI Framework to Optimize the Recruitment Screening Process," International Journal of Global Business and Competitiveness, Springer, vol. 18(1), pages 38-53, December.
    8. Hu, Qian & Pan, Zhao, 2023. "Can AI benefit individual resilience? The mediation roles of AI routinization and infusion," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    9. Gao, Wei & Jiang, Ning & Guo, Qingqing, 2023. "How do virtual streamers affect purchase intention in the live streaming context? A presence perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    10. Rana, Nripendra P. & Pillai, Rajasshrie & Sivathanu, Brijesh & Malik, Nishtha, 2024. "Assessing the nexus of Generative AI adoption, ethical considerations and organizational performance," Technovation, Elsevier, vol. 135(C).
    11. Janarthanan Balakrishnan & Yogesh K. Dwivedi & Laurie Hughes & Frederic Boy, 2024. "Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model," Information Systems Frontiers, Springer, vol. 26(3), pages 921-942, June.
    12. Wu, Min & Wang, Nanxi & Yuen, Kum Fai, 2023. "Can autonomy level and anthropomorphic characteristics affect public acceptance and trust towards shared autonomous vehicles?," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    13. Manu Sharma & Sudhanshu Joshi & Sunil Luthra & Anil Kumar, 2024. "Impact of Digital Assistant Attributes on Millennials’ Purchasing Intentions: A Multi-Group Analysis using PLS-SEM, Artificial Neural Network and fsQCA," Information Systems Frontiers, Springer, vol. 26(3), pages 943-966, June.

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