A Conceptual Model of Trust, Perceived Risk, and Reliance on AI Decision Aids

Solberg, Elizabeth; Kaarstad, Magnhild; Eitrheim, Maren Helene Rø; Bisio, Rossella; Reegård, Kine; Bloch, Marten

doi:10.1177/10596011221081238

Cited by 24 publications

(14 citation statements)

References 76 publications

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“…The study's results reveal that perceived risk significantly impacts attitudes toward AI, ethical concerns, and perceived trust. Therefore, perceived risk plays a crucial role in the model, and it is a key aspect concerning the acceptance of AI, which is aligned with previous studies [55,80]. In addition, it suggests a significant association between perceived risk, ethical concerns, and social norms, where ethical concerns are the primary driver of social norms.…”

Section: -5-discussionsupporting

confidence: 84%

Artificial Intelligence and Its Ethical Implications for Marketing

Gonçalves

Pinto²,

Rita³

et al. 2023

Emerg Sci J

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Despite the recent developments in AI, ethical questions arise when consumers contemplate how their data is being treated. This paper develops a conceptual model building on the theory of acceptance, risk, trust, and attitudes towards AI to understand the drivers that lead consumers to accept AI, considering consumers' ethical concerns. The model was empirically tested with 200 consumers of AI marketing services. The findings reveal that perceived risk significantly impacts attitudes toward AI, ethical concerns, and perceived trust and suggest a significant association between perceived risk, ethical concerns, and social norms. This research provides important theoretical and managerial implications for the ethical aspects of AI in marketing by highlighting the ethical and moral questions surrounding AI's acceptance. Doi: 10.28991/ESJ-2023-07-02-01 Full Text: PDF

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Section: -5-discussionsupporting

confidence: 84%

Artificial Intelligence and Its Ethical Implications for Marketing

Gonçalves

Pinto²,

Rita³

et al. 2023

Emerg Sci J

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“…Risk perception, acceptance, and trust may interact with each other and other factors stemming from professional, technological, and personal sources. The conceptual framework presented in Figure 1 illustrates the intricate interplay among sociodemographic variables, AI acceptance, trust, perceived risk, and outcomes [ 22 ]. Our study aims to contribute to this understanding not by testing individual relationships within this conceptual framework but by exploring how trust, risk, and acceptance are possibly interconnected in the context of AI-supported applications in gastroenterology.…”

Section: Methodsmentioning

confidence: 99%

Risk Perception, Acceptance, and Trust of Using AI in Gastroenterology Practice in the Asia-Pacific Region: Web-Based Survey Study

Goh,

Chia,

Cheung

et al. 2024

JMIR AI

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Background The use of artificial intelligence (AI) can revolutionize health care, but this raises risk concerns. It is therefore crucial to understand how clinicians trust and accept AI technology. Gastroenterology, by its nature of being an image-based and intervention-heavy specialty, is an area where AI-assisted diagnosis and management can be applied extensively. Objective This study aimed to study how gastroenterologists or gastrointestinal surgeons accept and trust the use of AI in computer-aided detection (CADe), computer-aided characterization (CADx), and computer-aided intervention (CADi) of colorectal polyps in colonoscopy. Methods We conducted a web-based questionnaire from November 2022 to January 2023, involving 5 countries or areas in the Asia-Pacific region. The questionnaire included variables such as background and demography of users; intention to use AI, perceived risk; acceptance; and trust in AI-assisted detection, characterization, and intervention. We presented participants with 3 AI scenarios related to colonoscopy and the management of colorectal polyps. These scenarios reflect existing AI applications in colonoscopy, namely the detection of polyps (CADe), characterization of polyps (CADx), and AI-assisted polypectomy (CADi). Results In total, 165 gastroenterologists and gastrointestinal surgeons responded to a web-based survey using the structured questionnaire designed by experts in medical communications. Participants had a mean age of 44 (SD 9.65) years, were mostly male (n=116, 70.3%), and mostly worked in publicly funded hospitals (n=110, 66.67%). Participants reported relatively high exposure to AI, with 111 (67.27%) reporting having used AI for clinical diagnosis or treatment of digestive diseases. Gastroenterologists are highly interested to use AI in diagnosis but show different levels of reservations in risk prediction and acceptance of AI. Most participants (n=112, 72.72%) also expressed interest to use AI in their future practice. CADe was accepted by 83.03% (n=137) of respondents, CADx was accepted by 78.79% (n=130), and CADi was accepted by 72.12% (n=119). CADe and CADx were trusted by 85.45% (n=141) of respondents and CADi was trusted by 72.12% (n=119). There were no application-specific differences in risk perceptions, but more experienced clinicians gave lesser risk ratings. Conclusions Gastroenterologists reported overall high acceptance and trust levels of using AI-assisted colonoscopy in the management of colorectal polyps. However, this level of trust depends on the application scenario. Moreover, the relationship among risk perception, acceptance, and trust in using AI in gastroenterology practice is not straightforward.

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“…For example, perceived trust influences the BI of intelligent healthcare services [78]. Solberg et al proposed a conceptual model of perceived risk and dependence for AI decision making that helps researchers to study trust and dependence on AI decision aids [79]. Thus, we propose the following hypothesis:…”

Section: Perceived Trust (Pt)mentioning

confidence: 99%

Everyone's an Artist? Exploring User Acceptance of AI-Based Painting Systems

Xu¹,

Zhang²,

Li³

et al. 2023

Preprint

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Artificial intelligence (AI) applications in different fields are developing rapidly, among which AI painting technology, as an emerging technology, has received wide attention from users for its creativity and efficiency. This study aimed to investigate the factors that influence user acceptance of the use of AIBPS by proposing an extended model that combines the Extended Technology Acceptance Model (ETAM) with the AI-based Painting System (AIBPS).A questionnaire was administered to 528 Chinese participants, using validated factor analysis data and Structural Equation Modeling (SEM) was used to test the hypotheses. The findings showed that hedonic motivation (HM) and perceived trust (PE) had a positive effect (+) on users' perceived usefulness (PU) and perceived ease of use (PEOU), while previous experience (PE) and technical features (TF) had no effect (-) on users' perceived usefulness (PU). This study provides an important contribution to the literature on AIBPS and the evaluation of systems of the same type, which helps to promote the sustainable development of AI in different domains and provides a possible space for further extension of TAM, thus helping to improve the user experience of AIBPS. The results of the study provide insights for system developers and enterprises to better motivate users to use AIBPS.

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A Conceptual Model of Trust, Perceived Risk, and Reliance on AI Decision Aids

Cited by 24 publications

References 76 publications

Artificial Intelligence and Its Ethical Implications for Marketing

Artificial Intelligence and Its Ethical Implications for Marketing

Risk Perception, Acceptance, and Trust of Using AI in Gastroenterology Practice in the Asia-Pacific Region: Web-Based Survey Study

Everyone's an Artist? Exploring User Acceptance of AI-Based Painting Systems

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