A series of three studies conducted in China explored the connection between how connected people feel to others and robot anthropomorphism (their tendency to see robots as having human-like qualities). The researchers found that when individuals felt more socially connected, they were more likely to think of robots as having human traits. This was especially true for people who were genuinely interested in interacting with robots. The research was published in Social Psychological and Personality Science.
Anthropomorphism is the tendency to attribute human-like characteristics, emotions, intentions, or behaviors to non-human entities, such as animals, objects, or even natural phenomena. Anthropomorphism can serve as a way for humans to relate to and explain the behaviors of non-human things. However, these attributes may not accurately reflect the true nature of the entity and can lead to misunderstandings or misinterpretations. Anthropomorphism is common in literature, art, advertising, and everyday conversations.
As the use of robots becomes widespread, robot anthropomorphism becomes increasingly common. For example, people often see robot companions as caring. Individuals prone to robot anthropomorphism are more likely to behave in a prosocial way towards robots and to have ethical considerations when dealing with them. But what determines whether people will attribute human characteristics to robots or not?
Study authors Jianning Dang and Li Liu wanted to find out. They hypothesized that social connectedness might promote robot anthropomorphism. Social connectedness is a sense of acceptance and connection with others. Highly socially connected individuals feel closeness with their social environment. This feeling might, in turn, make individuals genuinely more interested in social relationships as they will see them as positive and satisfying. If this genuine interest in social interactions is extended to robots, it can be expected to promote robot anthropomorphism because perceiving robots as having humanness or mind is a prerequisite for establishing social relationships with them. These researchers conducted three different studies to explore this idea.
In the first study, the researchers gathered 299 Chinese adults, and they split them into three groups. One group was made to feel socially connected, another disconnected, and the last one was a control group. The researchers did this by asking them to think about times they felt connected or disconnected from others. After that, they showed them a short video where a man knocked over a robot, and they asked the participants how much they thought the robot could think, feel pain, or have free will. This helped them measure how much the participants saw the robot as human-like.
In the second study, the researchers took 200 different Chinese adults and randomly assigned into them into one of two groups. One group was made to feel socially connected using the method from study 1 and the other was a control. They wanted to know if feeling connected to others made people more interested in interacting with robots. So, they asked them about their interest in human-robot interactions. After that, the researchers presented them with pictures and descriptions of a robot receptionist (Xiaody, designed to improve convenience and efficiency) and a companion robot (Lovot, designed to enhance levels of comfort and feelings of love). Participants reported how much they attribute human properties to these two robots (in the same way as in study 1). They also asked if they supported more research on those robots.
For the third study, the researchers tried to see if they could make people more interested in interacting with robots and then see if that made them think of robots as more human-like. They had some participants agree with statements that would make them more interested and others disagree with those statements. Then they gave them fake feedback, saying they either had high or low interest in interacting with robots. This was to see if changing their interest in robots would change how human-like they thought the robots were.
The results showed that all experimental manipulations researchers used were successful. In the first study, participants who were made to feel socially connected reported higher levels of robot anthropomorphism than participants in the control group or in the group that was made to feel socially disconnected. The control group and the socially disconnected group showed similar levels of robot anthropomorphism. This effect of high social connectedness on robot anthropomorphism remained even after researchers controlled for positive affect.
In the second study, the results supported a statistical model proposing that social connectedness enhanced the genuine interest for social interactions with robots. This genuine interest for social interaction with robots, in turn, enhanced robot anthropomorphism. Participants who reported higher level of anthropomorphism were more supportive of further research into both types of robots.
Finally, results of the third study showed that participants who were induced to higher genuine interest in social interactions with robots were more prone to attribute human properties to both types of robots compared to participants who were made to feel less interested in these interactions.
“Drawing on the motivated anthropomorphism approach, the present research revealed that social connectedness promotes people’s genuine interest in robots, which in turn facilitates their tendencies toward anthropomorphizing robots,” study authors concluded.
The study makes an important contribution to the scientific understanding of human-robot interactions. However, it also has limitations that need to be considered. Notably, none of the three studies included real interactions with robots. Participants only imagined robots based on pictures, descriptions or a very short video the researchers presented. Results might not be the same if participants interacted with real robots.
The study, “Social Connectedness Promotes Robot Anthropomorphism”, was authored by Jianning Dang and Li Liu.