Abstract
As an emerging market for voice assistants (VA), the healthcare sector imposes increasing requirements on the users’ trust in the technological system. To encourage patients to reveal sensitive data requires patients to trust in the technological counterpart. In an experimental laboratory study, participants were presented a VA, which was introduced as either a “specialist” or a “generalist” tool for sexual health. In both conditions, the VA asked the exact same health-related questions. Afterwards, participants assessed the trustworthiness of the tool and further source layers (provider, platform provider, automatic speech recognition in general, data receiver) and reported individual characteristics (disposition to trust and disclose sexual information). Results revealed that perceiving the VA as a specialist resulted in higher trustworthiness of the VA and of the provider, the platform provider and automatic speech recognition in general. Furthermore, the provider’s trustworthiness affected the perceived trustworthiness of the VA. Presenting both a theoretical line of reasoning and empirical data, the study points out the importance of the users’ perspective on the assistant. In sum, this paper argues for further analyses of trustworthiness in voice-based systems and its effects on the usage behavior as well as the impact on responsible design of future technology.
Highlights
Voice-based artificial intelligence systems serving as digital assistants have evolved dramatically within the last few years
The present paper showed for the first time that a short written introduction and a “spoken” introduction presented by the voice assistants (VA) itself were sufficient to affect the users’ perception and their trust in the system significantly
In line with previous studies, the present results revealed that participants, who perceive the VA tool as a specialist tool, reported higher levels of trustworthiness across all different source layers—compared to participants, who perceived the tool as a generalist
Summary
Voice-based artificial intelligence systems serving as digital assistants have evolved dramatically within the last few years. Their constituting features to recognize, process, and produce human language results in this technology to resemble human-human interaction. Reeves and Nass (1996) transferred the analysis of expertise and trust to human-technology interactions. They showed that designating devices (here: a television program) as “specialized” results in more positive evaluations of the content they presented. Many other studies replicated their approach and framed a technological device or a technological agent as a specialist showing that users ascribed a certain level of expertise and evaluated it (implicitly) as more trustworthy (Koh and Sundar, 2010; Kim, 2014, Kim, 2016; Liew and Tan, 2018)
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