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. 2024 Mar 25;10(7):e28562.
doi: 10.1016/j.heliyon.2024.e28562. eCollection 2024 Apr 15.

Expectation management in AI: A framework for understanding stakeholder trust and acceptance of artificial intelligence systems

Marjorie Kinney  1 , Maria Anastasiadou  1 , Mijail Naranjo-Zolotov  1 , Vitor Santos  1
Affiliations

Expectation management in AI: A framework for understanding stakeholder trust and acceptance of artificial intelligence systems

Marjorie Kinney et al. Heliyon. .

Abstract

As artificial intelligence systems gain traction, their trustworthiness becomes paramount to harness their benefits and mitigate risks. This study underscores the pressing need for an expectation management framework to align stakeholder anticipations before any system-related activities, such as data collection, modeling, or implementation. To this end, we introduce a comprehensive framework tailored to capture end-user expectations specifically for trustworthy artificial intelligence systems. To ensure its relevance and robustness, we validated the framework via semi-structured interviews, encompassing questions rooted in the framework's constructs and principles. These interviews engaged fourteen diverse end users across the healthcare and education sectors, including physicians, teachers, and students. Through a meticulous qualitative analysis of the interview transcripts, we unearthed pivotal themes and discerned varying perspectives among the interviewee groups. Ultimately, our framework stands as a pivotal tool, paving the way for in-depth discussions about user expectations, illuminating the significance of various system attributes, and spotlighting potential challenges that might jeopardize the system's efficacy.

Keywords: AI development process; AI in education; AI in health; Artificial intelligence; Expectation management; Explainable AI; Machine learning; Trustworthy AI.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Workflow of the AI expectation management framework use.
See this image and copyright information in PMC

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