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How Do Users Feel When They Use Artificial Intelligence for Decision Making? A Framework for Assessing Users’ Perception

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  • Amit Kumar Kushwaha

    (Indian Institute of Technology Delhi)

  • Ruchika Pharswan

    (Indian Institute of Technology Delhi)

  • Prashant Kumar

    (Indian Institute of Technology Delhi)

  • Arpan Kumar Kar

    (Indian Institute of Technology Delhi)

Abstract

Artificial intelligence (AI) transits from merely adopted technology to fueling everyday decision-making systems from medication to navigation. With this combination of AI in decision-making systems (ADMS), the present study explores how text-based users' data from social media helps organize the users' perspectives of ADMS? To investigate our research questions, we used a framework consisting of three phases, exploratory, confirmatory, and validatory. We applied hierarchy clustering and topic modeling in the exploratory study, hypothesis building, and empirical analysis during the confirmatory study and support vector machine (SVM) in the validatory study. Our findings suggest that users are primarily concerned about the risk involved in using ADMS. Factors like accountability, self-efficacy, knowledge of ADMS individuals' attitudes towards ADMS impact the perception of ADMS among individuals. This study's theoretical and practical implications have great scope as ADMS is still in its elementary stage.

Suggested Citation

  • Amit Kumar Kushwaha & Ruchika Pharswan & Prashant Kumar & Arpan Kumar Kar, 2023. "How Do Users Feel When They Use Artificial Intelligence for Decision Making? A Framework for Assessing Users’ Perception," Information Systems Frontiers, Springer, vol. 25(3), pages 1241-1260, June.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:3:d:10.1007_s10796-022-10293-2
    DOI: 10.1007/s10796-022-10293-2
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