人与AI对智能家居机器人的安全信任及其影响因素

doi:10.3724/SP.J.1041.2025.1951

摘要/Abstract

摘要：

随着智能家居机器人技术的发展, 安全风险成为人机信任的新挑战。本研究提出并验证了智能家居机器人信任的新维度——安全信任。为此, 研究1编制了智能家居机器人安全信任量表, 并验证了人机信任三因子结构的稳定性和信效度。研究2和研究3, 深入分析了机器人的静态和动态特征对人类与人工智能(AI)使用者安全信任的影响。结果发现, 在静态特征上, 人们对身高较矮以及摄像头不明显的机器人安全信任水平更高; 并且机器人拟人化程度影响了人类对这些静态特征的敏感性。在动态特征上, 机器人较慢的运动速度和摄像头关闭动作提高了人类的安全信任, 同时, 不同场景下这些动态特征的影响存在差异。此外, AI与人类在安全信任上表现出一定的一致性, 但总体上AI对机器人摄像头的敏感度低于人类。本研究结果为家居机器人的设计与制造提供了重要的理论支持和实践指导。

关键词: 人机信任, 安全信任, 智能家居机器人, 使用意愿, 大语言模型

Abstract:

As a result of the rapid development of intelligent domestic robot technology, safety concerns have emerged as a new challenge in human‒robot trust dynamics. This study explores and validates novel critical dimensions of trust that influence human and AI users’ perceptions of intelligent domestic robots, with a particular focus on safety trust. The research involves three comprehensive studies, each of which addresses different aspects of these dimensions.

In Study 1, we developed a safety trust scale pertaining specifically to intelligent domestic robots. This scale was rigorously tested to confirm the stability and validity of its three-dimensional structure, which included performance, relational, and safety trust. The scale’s psychometric properties were evaluated on the basis of factor analysis and reliability testing, thereby ensuring that it could accurately measure trust across different contexts and populations.

Study 2 explored the static characteristics of robots, such as their anthropomorphism, their height, and the visibility of their embedded cameras. We revealed that human participants exhibited higher levels of safety trust toward robots that were shorter in height and had fewer conspicuous cameras. Interestingly, the degree of anthropomorphism was determined to play a significant role in determining participants’ sensitivity to these static features.

Study 3 expanded the investigation to encompass the dynamic characteristics of robots, such as movement speed, interaction scenario and camera operation (i.e., turning the camera off). The results indicated that slower-moving robots were generally perceived as safer, and higher levels of safety trust were attributed to them. Moreover, the action of turning off a robot’s camera during interactions was observed to significantly enhance safety trust among human users. The study also highlighted the fact that the influence of these dynamic features varied across different interaction scenarios, thus suggesting that situational factors play crucial roles in shaping trust perceptions.

Furthermore, a comparative analysis between human and AI users revealed a certain degree of consistency in safety trust judgments. Both human and AI users were generally aligned in terms of their trust assessments on the basis of both static and dynamic robot features. However, the AI’s sensitivity to the visibility of robot cameras was notably lower than that of humans, thus suggesting that AI may prioritize different factors in the context of assessing safety trust.

Overall, the findings of this research provide valuable insights into the design and manufacturing of intelligent domestic robots, including by emphasizing the importance of considering both static and dynamic features in the process of enhancing safety trust. The results also offer theoretical and practical guidance for the development of trust models that can be applied in various intelligent home environments, thereby ultimately contributing to the advancement of human‒robot interactions.

Key words: human-robot trust, safety trust, intelligent domestic robots, user intention, LLM

中图分类号:

B849: C91

由姗姗, 齐玥, 陈俊廷, 骆磊, 张侃. (2025). 人与AI对智能家居机器人的安全信任及其影响因素. 心理学报, 57(11), 1951-1972.

YOU Shanshan, QI Yue, CHEN JunTing, LUO Lei, ZHANG Kan. (2025). Safety trust in intelligent domestic robots: Human and AI perspectives on trust and relevant influencing factors. Acta Psychologica Sinica, 57(11), 1951-1972.

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因变量	增加信任		降低信任		自变量	F	η²_p
因变量	前测	后测	前测	后测	自变量	F	η²_p
安全信任 (自编)	4.10 (0.10)	4.33 (0.08)	3.77 (0.10)	2.08 (0.08)	改变方向	155.61^***	0.55
					前后测	2.01	0.02
					改变方向 × 前后测	151.61^***	0.54
关系信任 (自编)	4.27 (0.06)	4.41 (0.08)	4.13 (0.06)	2.30 (0.08)	改变方向	254.01^***	0.67
					前后测	0.20	<0.01
					改变方向 × 前后测	194.42^***	0.61
性能信任 (自编)	4.43 (0.03)	4.49 (0.10)	4.38 (0.03)	2.87 (0.10)	改变方向	124.08^***	0.49
					前后测	3.23	0.03
					改变方向 × 前后测	109.49^***	0.46
总体信任 (自编)	4.24 (0.07)	4.44 (0.08)	4.13 (0.07)	2.16 (0.08)	改变方向	252.52^***	0.67
					前后测	0.51	0.04
					改变方向 × 前后测	254.81^***	0.67
人机信任 (Jian et al., 2000)	4.08 (0.04)	4.17 (0.06)	3.94 (0.04)	2.38 (0.06)	改变方向	337.18^***	0.73
					前后测	1.22	0.01
					改变方向 × 前后测	295.82^***	0.70
使用意愿 (Gursoy et al., 2019)	4.53 (0.23)	4.64 (0.20)	4.44 (0.28)	2.21 (0.82)	改变方向	487.53^***	0.80
					前后测	8.49^**	0.06
					改变方向 × 前后测	420.84^***	0.77

因变量	增加信任		降低信任		自变量	F	η²_p
因变量	前测	后测	前测	后测	自变量	F	η²_p
安全信任 (自编)	4.10 (0.10)	4.33 (0.08)	3.77 (0.10)	2.08 (0.08)	改变方向	155.61^***	0.55
					前后测	2.01	0.02
					改变方向 × 前后测	151.61^***	0.54
关系信任 (自编)	4.27 (0.06)	4.41 (0.08)	4.13 (0.06)	2.30 (0.08)	改变方向	254.01^***	0.67
					前后测	0.20	<0.01
					改变方向 × 前后测	194.42^***	0.61
性能信任 (自编)	4.43 (0.03)	4.49 (0.10)	4.38 (0.03)	2.87 (0.10)	改变方向	124.08^***	0.49
					前后测	3.23	0.03
					改变方向 × 前后测	109.49^***	0.46
总体信任 (自编)	4.24 (0.07)	4.44 (0.08)	4.13 (0.07)	2.16 (0.08)	改变方向	252.52^***	0.67
					前后测	0.51	0.04
					改变方向 × 前后测	254.81^***	0.67
人机信任 (Jian et al., 2000)	4.08 (0.04)	4.17 (0.06)	3.94 (0.04)	2.38 (0.06)	改变方向	337.18^***	0.73
					前后测	1.22	0.01
					改变方向 × 前后测	295.82^***	0.70
使用意愿 (Gursoy et al., 2019)	4.53 (0.23)	4.64 (0.20)	4.44 (0.28)	2.21 (0.82)	改变方向	487.53^***	0.80
					前后测	8.49^**	0.06
					改变方向 × 前后测	420.84^***	0.77

	女	男	18~25岁	26~35岁	36~45岁	46~60岁
研究1a编制阶段	988	505	30%	36%	29%	5%
研究1a验证阶段	286	147	12%	72%	11%	5%
研究1b增加信任组	43	22	11%	71%	15%	3%
研究1b降低信任组	42	23	18%	74%	6%	2%

	女	男	18~25岁	26~35岁	36~45岁	46~60岁
研究1a编制阶段	988	505	30%	36%	29%	5%
研究1a验证阶段	286	147	12%	72%	11%	5%
研究1b增加信任组	43	22	11%	71%	15%	3%
研究1b降低信任组	42	23	18%	74%	6%	2%

	分组	女	男	18~30岁	31~40岁	41~60岁
研究2a	机械外观组	142	98	45%	49%	6%
	卡通外观组	140	100	45%	48%	7%
	真人外观组	170	70	35%	60%	5%