Trust and acceptance of AI caregiving robots: The role of ethics and self-efficacy

Abstract

As AI technology rapidly advances, ethical concerns have emerged as a global focus. This study introduces a second-order scale for analyzing AI ethics and proposes a model to examine the intention to use AI caregiving robots. The model incorporates elements from the Unified Theory of Acceptance and Use of Technology (UTAUT)—including social influence and performance expectancy—alongside AI ethics, self-efficacy, and trust in AI. The findings reveal that AI ethics and social influence enhance self-efficacy, which in turn increases trust in AI, performance expectancy, and the intention to use AI caregiving robots. Moreover, trust in AI and performance expectancy directly and positively influence the intention to adopt these robots. By incorporating AI ethics, the model provides a more comprehensive perspective, addressing dimensions often overlooked in conventional models. The proposed model is validated across diverse samples, demonstrating both its theoretical and practical significance in predicting AI usage intentions. • Introduces a second-order scale to analyze AI ethics in caregiving robots. • Model integrates AI ethics, UTAUT, self-efficacy, and trust in AI. • AI ethics and social influence boost self-efficacy and trust in AI. • Trust in AI and performance expectancy drive AI caregiving robot adoption. • Model validated across samples, offering theoretical and practical insights.