This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: As AI continues to develop at a rapid pace, social robots powered by AI are becoming more commonplace in customer service settings such as retail, hospitality, tourism and health care. But as these robots become smarter and appear more human, little attention has been given to how this might affect the consumers interacting with them.
Now, research from the University of Birmingham (UK), Aarhus University (Denmark), and Linnaeus University (Sweden) has found that interacting with robots displaying human-like behaviors, such as adaptive learning, personalized communication and empathetic engagement, can reinforce, reshape or destabilize a consumer's self-perception. The research has been published in the journal AI & Society. Inci Toral-Manson, associate professor of marketing at the University of Birmingham, said, "Social robots in customer service settings are designed to mimic gestures, speech and emotional cues to elicit cognitive and emotional responses from customers.
Our research explores how dealing with these anthropomorphized robots can create a bidirectional influence, where robots become more like people, and people become more like robots, which we call 'robotoid humanness.'" The researchers set out a framework of human-robot interactions and how they can influence self-discovery and self-perception. This framework includes the service setting, consumer expectations, the robot's appearance and speech and, crucially, the commitments (actions) of the consumer and robot. To foster engagement with people, customer service robots use AI and learning models to mimic human behavior.
This aims to instill trust and achieve the best customer engagement. People use social cues from those they interact with, often subconsciously imitating others' behaviors or expressions, also known as mirroring. It is between the two actions in the framework that mirroring and mimicry come into effect.
Selcen Ozturkcan, associate professor of business administration at Linnaeus University, explained: "The consumer acts, the robot responds, and with repeated exposure, over time the consumer internalizes the exchange. Machine learning and AI can amplify this process, adjusting robot behavior based on user input and enabling more personalized and human-like mimicry from the robot. For people, the innate instinct to mirror can lead them to reciprocate the robot's communicative behaviors, making them more robot-like." The study argues that this mirroring can raise ethical concerns, as persistent mimicry can lead to a mimicking-mirroring feedback loop in which consumer identity is shaped.
It can also be constrained by repeated exposure to algorithmically driven feedback, causing confirmation bias and other negative outcomes. These repeated interactions can also change an individual's self-perception depending on factors such as technological readiness, cultural background and personality traits. This raises ethical questions, especially when there may be a risk of people depending on robots for validation of their self-worth, as repeated positive reinforcement can enhance consumers' confidence, while negative cues may lower self-esteem.
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