不良研究所

Artificial intelligence chatbots that show positive feelings 鈥� such as adding an 鈥淚 am excited to do so!鈥� or a few exclamation marks 鈥� do not necessarily translate into positive reactions or contribute to higher customer satisfaction, according to a recent study by researchers from the University of South Florida, the Georgia Institute of Technology and 不良研究所.

As online retailers increasingly use artificial intelligence chatbots to streamline customer service tasks and replace their human counterparts, the researchers examined how emotion-expressing AI chatbots can impact customer service.

鈥淚t is commonly believed and repeatedly shown that human employees can express positive emotion to improve customers鈥� service evaluations. However, our findings suggest that this conventional wisdom does not necessarily apply to the case of an AI service agent,鈥� said study co-author and 不良研究所 Professor Elizabeth Han, Desautels Faculty of Management.

The research is particularly relevant with the rise of emotional AI 鈥� the branch that deals with processing and replicating human emotions 鈥� and the recent claim from a Google engineer that an unreleased AI chatbot was 鈥渟entient.鈥�

That claim and the resulting backlash led to the employee鈥檚 firing for violating employment and data security policies. In addition, a national debate ensued around what 鈥渟entient鈥� means and whether Google鈥檚 chatbot has consciousness or feelings.

In order to bring real-world applications to the debate, the study explored how customers make sense of and react to positive emotions from an AI chatbot when compared to a human customer service agent.

The researchers say impactful research is needed in emotional AI technologies, because the industry is projected to grow to $100 billion by 2024 and $200 billion by 2026, according to market research from Global Industry Analysts and Reports and Data.

Customers鈥� expectations play an important role

The researchers conducted three experiments using emotion-capable chatbots in a customer service scenario.

In the first test, participants interacted with either an AI or human customer service agent to resolve a hypothetical service issue. Half the participants chatted with an agent where positive adjectives and exclamation marks were added into its responses, such as 鈥淚 am delighted to handle your request today!鈥�

The remainder of the group chatted with an agent without any emotions, such as 鈥淚 am handling your request today.鈥� Participants rated the customer service quality and satisfaction on a seven-point scale.

The experiments revealed some surprising findings:

• While positive emotions from a human are beneficial and increase customer satisfaction, the same emotions from an AI chatbot are not as effective.
• Customers鈥� expectations play an important role, as they don鈥檛 expect an AI chatbot to be able to feel emotion. Too much chatbot positivity can be a turn-off for consumers and lead to negative reactions.

The work further expands the understanding of customers鈥� reactions to emotional AIs as well as gives companies guidance on how and when retailers should use emotion-capable AI service agents.

Researchers cautioned that companies should understand the expectations of customers exposed to AI-powered services before haphazardly equipping AIs with emotion-expressing capabilities.

Other major takeaways from the study include:

• Good feelings can spread from a human agent鈥檚 positive emotional expressions to a customer, and the same can occur for an AI-powered chatbot. But sometimes those good feelings are cancelled out by a negative reaction to not expecting chatbots to display emotions.
• Expectations play an important role on whether an AI chatbot expressing positive emotions is a positive or negative experience. Different types of customers will react to the same AI-expressed emotions differently.

Servion Global Solutions predicts that by 2025, AI will drive 95% of all customer interactions, including live phone calls and online conversations, according to Finance Digest.

鈥淥ur work reveals the unique impact of expressed positive emotion by an AI agent on customers鈥� service evaluations along with the underlying mechanisms and a boundary condition, thus opening up exciting research opportunities in the area of human-AI interaction,鈥� Han said.

Researchers conducted the experiments at the Muma College of Business at USF and at the Scheller College of Business at the Georgia Institute of Technology through in-person and online lab sessions from 2019 to 2020.

Aside from Han, the article鈥檚 co-authors include Denny Yin, University of South Florida, and Han Zhang, Georgia Institute of Technology.

鈥淭o our knowledge, this research is the very first to explore the ramifications of equipping service AI agents with emotional expression capabilities,鈥� Yin said. 鈥淲e found that people react more negatively when the service agent is a bot instead of a human. The reason is that people do not expect chatbots to have feelings.鈥�

The article co-authored by Elizabeth Han, Assistant Professor in the Desautels Faculty of Management, was recently published in Information Systems Research.

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