Ghazali Aimi S, Ham Jaap, Barakova Emilia I, Markopoulos Panos
Department of Industrial Design, Eindhoven University of Technology, Eindhoven, Netherlands.
Department of Mechatronics Engineering, International Islamic University Malaysia, Selayang, Malaysia.
Front Robot AI. 2018 Jun 21;5:73. doi: 10.3389/frobt.2018.00073. eCollection 2018.
The growing interest in social robotics makes it relevant to examine the potential of robots as persuasive agents and, more specifically, to examine how robot characteristics influence the way people experience such interactions and comply with the persuasive attempts by robots. The purpose of this research is to identify how the (ostensible) gender and the facial characteristics of a robot influence the extent to which people trust it and the psychological reactance they experience from its persuasive attempts. This paper reports a laboratory study where SociBot™, a robot capable of displaying different faces and dynamic social cues, delivered persuasive messages to participants while playing a game. In-game choice behavior was logged, and trust and reactance toward the advisor were measured using questionnaires. Results show that a robotic advisor with upturned eyebrows and lips (features that people tend to trust more in humans) is more persuasive, evokes more trust, and less psychological reactance compared to one displaying eyebrows pointing down and lips curled downwards at the edges (facial characteristics typically not trusted in humans). Gender of the robot did not affect trust, but participants experienced higher psychological reactance when interacting with a robot of the opposite gender. Remarkably, mediation analysis showed that liking of the robot fully mediates the influence of facial characteristics on trusting beliefs and psychological reactance. Also, psychological reactance was a strong and reliable predictor of trusting beliefs but not of trusting behavior. These results suggest robots that are intended to influence human behavior should be designed to have facial characteristics we trust in humans and could be personalized to have the same gender as the user. Furthermore, personalization and adaptation techniques designed to make people like the robot more may help ensure they will also trust the robot.
对社交机器人日益增长的兴趣使得研究机器人作为有说服力的媒介的潜力变得很有意义，更具体地说，是研究机器人的特征如何影响人们体验这种互动的方式以及他们对机器人说服尝试的顺从程度。本研究的目的是确定机器人的（表面）性别和面部特征如何影响人们对它的信任程度以及他们在面对机器人的说服尝试时所体验到的心理抗拒。本文报告了一项实验室研究，在该研究中，能够展示不同面部表情和动态社交线索的SociBot™机器人在与参与者玩游戏时传递说服性信息。记录游戏中的选择行为，并使用问卷测量对顾问机器人的信任和抗拒程度。结果表明，与一个眉毛向下、嘴角向下卷曲（人类通常不信任的面部特征）的机器人相比，一个眉毛上扬、嘴唇上翘（人们往往更信任人类的这类特征）的机器人顾问更具说服力，能唤起更多信任，且引发的心理抗拒更少。机器人的性别不影响信任，但参与者在与异性机器人互动时会体验到更高的心理抗拒。值得注意的是，中介分析表明，对机器人的喜爱完全中介了面部特征对信任信念和心理抗拒的影响。此外，心理抗拒是信任信念的一个强大且可靠的预测指标，但不是信任行为的预测指标。这些结果表明，旨在影响人类行为的机器人应该设计成具有我们在人类身上所信任的面部特征，并且可以进行个性化设置，使其与用户性别相同。此外，旨在让人们更喜爱机器人的个性化和自适应技术可能有助于确保他们也会信任该机器人。
