First impressions of a financial AI assistant: differences between high trust and low trust users

Frontiers in Artificial Intelligence

Artificial Intelligence

Laura Moradbakhti¹  Simon Schreibelmayr¹  Martina Mara² 

[1] Robopsychology Lab, Linz Institute of Technology, Johannes Kepler University Linz, Linz, Austria;null;

关键词: human-AI interaction;    banking;    user perception;    trust calibration;    acceptance;    agency;    survey;   

DOI  :  10.3389/frai.2023.1241290

 received in 2023-06-16, accepted in 2023-09-05,  发布年份 2023

来源: Frontiers

【 摘 要 】

Calibrating appropriate trust of non-expert users in artificial intelligence (AI) systems is a challenging yet crucial task. To align subjective levels of trust with the objective trustworthiness of a system, users need information about its strengths and weaknesses. The specific explanations that help individuals avoid over- or under-trust may vary depending on their initial perceptions of the system. In an online study, 127 participants watched a video of a financial AI assistant with varying degrees of decision agency. They generated 358 spontaneous text descriptions of the system and completed standard questionnaires from the Trust in Automation and Technology Acceptance literature (including perceived system competence, understandability, human-likeness, uncanniness, intention of developers, intention to use, and trust). Comparisons between a high trust and a low trust user group revealed significant differences in both open-ended and closed-ended answers. While high trust users characterized the AI assistant as more useful, competent, understandable, and humanlike, low trust users highlighted the system's uncanniness and potential dangers. Manipulating the AI assistant's agency had no influence on trust or intention to use. These findings are relevant for effective communication about AI and trust calibration of users who differ in their initial levels of trust.

【 授权许可】

Unknown   
Copyright © 2023 Schreibelmayr, Moradbakhti and Mara.