Artificial Intelligence Is Trusted Less than a Doctor in Medical Treatment Decisions: Influence of Perceived Care and Value Similarity
Abstract
Artificial intelligence (AI) can provide many benefits in healthcare, including rapid and effective treatment options. However, previous research on human–computer interactions has demonstrated that people are reluctant to accept AI. This study compared individuals’ trust in AI with their trust in doctors regarding medical treatment and explored whether people trust an AI system that understands and suggests their desired treatments. We conducted an online experiment (N = 415) adopting a scenario method. The participants were asked to imagine receiving a medical examination and being prescribed medicine by a physician or an AI system. Participants trusted the AI system less than a doctor, even when the AI system learned and suggested their desired treatment. This finding confirms that people are reluctant to trust AI even if it performs at the level of a human doctor, thereby strengthening the existent literature that shows people prefer human doctors.
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Previous empirical studies on patients' acceptance or trust in AI are somewhat conflicting.
“The results of previous empirical studies on patients’ acceptance or trust in AI are somewhat conflicting. Some studies have shown that participants are more accepting of AI if it is proven to be more accurate than providers26,29 or if the use of AI fits societal and cultural norms.35,36 However, other studies have found that trust in AI did not increase when participants were informed that the AI”
From Patient perspectives on informed consent for medical AI: A web-based experiment (2024) · cites this paper as [52]
People prefer human to AI decision makers for diagnostic and prescription decisions.
“Yokoi et al. (2021), in their online scenario study, found that people prefer human to AI decision makers for diagnostic and prescription decisions.”
From Medical AI and human dignity: Contrasting perceptions of human and artificially intelligent (AI) decision making in diagnostic and medical resource allocation contexts (2022) · cites this paper as Yokoi et al., 2021
Existing literature shows that people prefer human decision makers over AI in various diagnostic contexts.
“Existing literature shows that people prefer human decision makers over AI in various diagnostic contexts (e.g., Lennartz et al., 2021;Yokoi et al., 2021).”
From Medical AI and human dignity: Contrasting perceptions of human and artificially intelligent (AI) decision making in diagnostic and medical resource allocation contexts (2022) · cites this paper as Yokoi et al., 2021
Physicians and healthcare professionals might be hesitant to trust AI-driven diagnoses or treatment recommendations, leading to slow adoption and resistance to change.
“Physicians and healthcare professionals might be hesitant to trust AI-driven diagnoses or treatment recommendations, leading to slow adoption and resistance to change (Yokoi et al., 2021).”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Yokoi et al., 2021
The adoption of new technologies, including AI, in the Indian pharmaceutical industry is influenced by cultural beliefs, practices, and socioeconomic factors.
“Furthermore, the adoption of new technologies, including AI, in the Indian pharmaceutical industry is influenced by cultural beliefs, practices, and socioeconomic factors.”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Yokoi et al., 2021
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- Authors
- Yokoi, R., Eguchi, Y., Fujita, T., & Nakayachi, K.
- Affiliations
- Doshisha University (JP)
- Keio University (JP)
- Corresponding author
- Eguchi, Yoko
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2020-12-26
- Volume
- 37
- Issue
- 10
- Pages
- 981-990
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W3117152754
- Cited by
- 122
- References
- 44
- Citations by year
- 2026: 24 · 2025: 31 · 2024: 28 · 2023: 22 · 2022: 11 · 2021: 5 · 2020: 1
- FWCI
- 2.91
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Human-Computer Interaction (publishedVersion)
- Funders
- Grant-in-Aid for Scientific Research
- Japan Society for the Promotion of Science
- Japan Science and Technology Agency
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Keywords
- trust in AI, trust in physicians, treatment decision-making, human-AI interaction, perceived care, value similarity
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