(Why) Do We Trust AI?: A Case of AI-based Health Chatbots

IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
A. V. Prakash, Saini Das
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引用次数: 0

Abstract

Automated chatbots powered by artificial intelligence (AI) can act as a ubiquitous point of contact, improving access to healthcare and empowering users to make effective decisions. However, despite the potential benefits, emerging literature suggests that apprehensions linked to the distinctive features of AI technology and the specific context of use (healthcare) could undermine consumer trust and hinder widespread adoption. Although the role of trust is considered pivotal to the acceptance of healthcare technologies, a dearth of research exists that focuses on the contextual factors that drive trust in such AI-based Chatbots for Self-Diagnosis (AICSD). Accordingly, a contextual model based on the trust-in-technology framework was developed to understand the determinants of consumers’ trust in AICSD and its behavioral consequences. It was validated using a free simulation experiment study in India (N = 202). Perceived anthropomorphism, perceived information quality, perceived explainability, disposition to trust technology, and perceived service quality influence consumers’ trust in AICSD. In turn, trust, privacy risk, health risk, and gender determine the intention to use. The research contributes by developing and validating a context-specific model for explaining trust in AICSD that could aid developers and marketers in enhancing consumers’ trust in and adoption of AICSD.
(我们为什么要信任人工智能?基于人工智能的健康聊天机器人案例
由人工智能(AI)驱动的自动聊天机器人可以充当无处不在的联络点,改善医疗保健的获取途径,使用户能够做出有效的决定。然而,尽管有潜在的好处,但新出现的文献表明,与人工智能技术的显著特征和特定使用环境(医疗保健)相关的忧虑可能会破坏消费者的信任并阻碍广泛采用。尽管信任在医疗保健技术的接受过程中扮演着关键的角色,但目前还缺乏对基于人工智能的自我诊断聊天机器人(AICSD)产生信任的背景因素的研究。因此,我们在技术信任框架的基础上建立了一个情境模型,以了解消费者对 AICSD 信任的决定因素及其行为后果。在印度进行的一项自由模拟实验研究(N = 202)对该模型进行了验证。感知拟人化、感知信息质量、感知可解释性、信任技术的倾向和感知服务质量影响消费者对 AICSD 的信任。反过来,信任、隐私风险、健康风险和性别又决定了使用意向。该研究通过开发和验证一个解释 AICSD 信任度的特定情境模型,帮助开发人员和营销人员提高消费者对 AICSD 的信任度和采用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Australasian Journal of Information Systems
Australasian Journal of Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
4.40
自引率
4.80%
发文量
20
审稿时长
20 weeks
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