Effects of communication style and culture on ability to accept recommendations from robots

Abstract

The objective of this paper is to investigate the effects of communication styles and culture on people’s accepting recommendations from robots. The goal was to provide insight for culturally adaptive robot design. The independent variables were communication style (i.e. implicit or explicit), the participants’ cultural background (i.e. Chinese or German), and the robot’s language (i.e. native language and English for Chinese and German subjects). A laboratory experiment was conducted with 16 Chinese and 16 German college students. Basic descriptive statistics and t-test are used for biographical information analysis; reliability test is used for questionnaire; MANOVA and non-parametric test are used for testing the hypotheses. The results showed that the Chinese participants preferred an implicit communication style than German participants. Chinese participants evaluated the robots as being more likable, trustworthy, and credible, and were more likely to accept the implicit recommendations. The German participants evaluated the robots as being less likable, trustworthy, and credible, and were less inclined to accept implicit recommendations.

Introduction

Social robots are a rapidly growing area of interest for researchers. The characteristics of social robots include the ability to interact with humans in ways that are more natural, through more complex understanding and exhibition of social cues that humans normally use in communication. Reeves and Nass in 1996 studied the interactions between humans and computers or televisions, and the results showed that even a minimal level of social cues present in an interface or technological artifact leads people to treat the system in a way psychologically similar to how they would treat another person. It can be expected that similar, but stronger effects will be found between the interactions between humans and social robots (Kidd, 2003). In human society, trust, and preference are important for people to accept recommendations from other people. When a robot acts as an advisor in public, these aspects are expected to influence people’s decisions.

Past studies about communication between humans have revealed that language has various functions for communicative behaviors (Patricia, 1997, Wolfram, 1997). Moreover, the influences of culture in communication have been investigated in linguistics and cultural anthropology. Culture underlies every aspect of social behavior and helps to define the rules and patterns of each language. Thus, individual communicative behaviors are reflective of one’s language and culture (Patricia, 1997).

If an agent is designed only according to the designers’ cultural background, the end users whose cultural background is different from the designers’ may suffer from the culturally biased communication. Such communication failures will impede system performance and consequently lower their evaluations. To solve this problem, the concept of culturally adaptive agents is introduced. Such agents have two features: firstly, having the ability to detect different forms of communicative behaviors, and secondly, can respond to them appropriately. The designers can only build up such agents by recognizing the cultural differences existing in the communications either between human and agents or between human and human, and then consider the differences when designing (Patricia, 1997).

Although many researchers have realized the influence of cultural differences in human–robot interaction, very few studies have been conducted to investigate this factor and no convincing explanations of these differences have been made. The majority of previous experiments carried out by researchers from America, Japan, the UK, and many other countries have mainly been based on the native population, and some of the conclusions may not be generalized to other cultures. Only by recognizing and considering such influences in the design of agents can robots communicate with people from cultures different from those of their designers without any cultural bias. Thus, the objective of this paper is to investigate how a robot’s language and communication style will influence people with different cultural backgrounds.