The Impact of Artificial Agents on Persuasion: A Construal Level Account

Tae Woo Kim and Adam Duhachek, 2018, 18-132-10

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With the remarkable progress of AI’s natural language processing, the next generation of AI is predicted to be an active agent that can persuade consumers to buy products and services. Whereas more firms are attempting to incorporate AI as a part of their marketing programs, little research has examined how such a program can be developed into an effective persuasion system.

The current research identifies a critical aspect of consumer perceptions of AI: humans do not perceive autonomous goals in artificial agents. Artificial agents are more likely to be perceived by humans as controlled by programmed algorithms rather than acting on their own intentions.

For example, few would say that Google’s AlphaGo, a computer program that plays the board game Go, has a goal to be a world Go champion. Rather, it is just programmed to play Go. In line with this perception, people focus on “how” rather than “why” AlphaGo plays the game. Consumers apply the same belief about lack of intention to Amazon Alexa, Apple’s Siri, and Google Duplex when they recommend products or services to humans.

Research has shown that persuasion is more effective when the perceived characteristics of the persuasion source and the persuasion message match. Thus, Tae Woo Kim and Adam Duhachek predict that AI’s persuasion is more effective when it highlights “how” rather than “why” in its persuasion message.

In a series of experiments, they show that an AI persuasion message is more effective in persuading consumers to buy the recommended product or services when the message highlights “how” to use or buy the product rather than “why” to use or buy the product. For example, an AI message encouraging the use of sunscreen made consumers intend to buy the sunscreen when the message highlighted “how” rather than “why” to use the sunscreen. These effects were observed because consumers doubt whether AI can understand “why” it is important for humans to engage in healthy behavior.

These effects were replicated in a few other contexts, such as doing exercise. Further, the authors found that these effects are moderated when people are informed that the AI can learn. In other words, people believe that artificial agents have a capability to learn to think about “why,” as well as “how.”

Tae Woo Kim is a Ph.D. candidate and Adam Duhachek is the Nestlé-Hustad Professor of Marketing, both at the Kelley School of Business, Indiana University.

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