Communication is a discipline with a focus on the study of messages. Research in communication enables the conceptualization and application of theories to help understand how technology can be more persuasive.
Influence, or persuasion, is how people are affected by communication. A “right” influence can alter people’s behavior for the better. For example, persuasive robots may help people quit smoking or take prosocial action.
A new technology allows a new way of communication. Our endeavor is to utilize technology to be more influential and to develop theories that help us understand the fundamental effects of communication, influence, and technology.
How can new communication technologies effectively influence people? To answer this question, we examine how theories of communication can take advantage of unique characteristics afforded by these technologies.
A robot can effectively get people to do as the robot asks by capitalizing on the norm of reciprocity and following with a verbal request. We found that 60% of participants who were helped by a robot in a trivia game just for five minutes returned the robot’s favor by completing boring tasks for 15 minutes, no matter they liked the robot or not. This compliance rate was significantly higher than that of those who were not helped by the robot (33%).
Why do people treat robots and computers as if they were humans? Probably because people operate on a kind of autopilot when they interact with technology. In our study, a computer agent requested participants to do boring tasks. Mindless participants compiled when any kind of reason was given with the magic word “because.” Attentive participants complied only when a proper reason was given.
Using a nationally representative sample, we found that 26% of US population report a heightened level of fear toward autonomous robots and artificial intelligence. This fear was connected to sex, age, education, and household income, as well as media exposure to science fiction. It is also related to other types of fear, such as loneliness, becoming unemployed, and drone use.
We examined the effects of user-generated content on human-robot trust as well as interaction outcomes. We found that reading online reviews about robot partners before interaction augmented the effects of human-robot trust on interaction outcomes. Specifically, it elicited positive mood and more favorable evaluations of the robot. This finding suggests that messages can be strategically deployed to enhance trust and interaction outcomes.
From factories, offices and medical centers to our homes, cars and even our local coffee shops, robots and artificial intelligence are playing an increasingly greater role in how we work, live and play...
Cincinnati Public Radio
October 3, 2017
As social robots permeate wide segments of our daily lives, they may become capable of influencing our attitudes, beliefs, and behaviors. In other words, robots may be able to persuade us, and this is already happening...
Cincinnati Business Courier
March 24, 2017
It’s no secret that the College of Informatics has the most technologically advanced building on campus — Griffin Hall. But Griffin Hall is also home to Pineapple. Dr. Lee and Dr. Liang are using Pineapple to conduct studies on how humans interact socially when a robot is present...
Between the studies on digital media production and computer sciences, Griffin Hall is home to some impressive technology. You might start seeing a new, digital face wandering the halls of the College of Informatics. That digital face is known as Pineapple, and it will be used for the next three years for research into social robotics...
October 19, 2015
Valerie Scudder Award: Jake Liang, Chapman University (2017)
Excellence in Research, Scholarship, and Creative Activity: Austin Lee, Northern Kentucky University (2017)
Faculty Research Excellence Award: Jake Liang, Chapman University (2016)
National Communication Association, Communication and the Future Division (Lee & Liang, 2017)
International Communication Association, Instructional and Developmental Communication Division (Liang, 2015)
Faculty Summer Fellowship (Robot Credibiilty): Austin Lee, Northern Kentucky University (2015)
Faculty Project Grant (Social Robotics): Austin Lee, Northern Kentucky University (2015)
Research Grant (Participatory Websites): Jake Liang, Chapman University (2015)
Seed Grant (Persuasive Robotics): Austin Lee, Northern Kentucky University (2015)
Lee, S. A., & Liang, Y. (2018). Theorizing verbally persuasive robots. In A. L. Guzman (Ed.), Human-machine communication: Rethinking communication, technology, and ourselves (pp. 119-143). New York, NY: Peter Lang.
Lee, S. A., & Liang, Y. (2018). Robotic foot-in-the-door: Using sequential-request persuasive strategies in human-robot interaction. Computers in Human Behavior.
Liang, Y., & Lee, S. A. (2017). Fear of autonomous robots: Evidence from national representative data with probability sampling. International Journal of Social Robotics, 9, 379-384.
Liang, Y., & Lee, S. A. (2016). Advancing the strategic messages affecting robot trust effect: The dynamic of user- and robot-generated content on human-robot trust and interaction outcomes. Cyberpsychology, Behavior, and Social Networking, 19, 538-544.
Lee, S. A., & Liang, Y. (2016). The role of reciprocity in verbally persuasive robots. Cyberpsychology, Behavior, and Social Networking. 19, 524-527.
Liang, Y., & Lee, S. A. (2016). Employing user-generated content to enhance human-robot interaction in a human-robot trust game. In Proceedings of the 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2016). Christchurch, New Zealand.
Lee, S. A., Liang, Y., & Cho, S. (2016). Effects of anthropomorphism and reciprocity in persuasive computer agents. Paper presented at the at the 102nd annual convention of the National Communication Association, Philadelphia, PA.
Cho, S., Lee, S. A., & Liang, Y. (2016). Using anthropomorphic agents for persuasion. Paper presented at the 66th annual convention of the International Communication Association, Fukuoka, Japan.
Lee. S. A., & Liang, Y. (2015). Reciprocity in computer-human interaction: Source-based, norm-based, and affect-based explanations. Cyberpsychology, Behavior, and Social Networking, 18, 234-240.
Liang, Y., Lee, S. A., & Jang, J. (2013). Mindlessness and gaining compliance in computer-human interaction. Computers in Human Behavior, 29, 1572-1579.
Lee, S. A., & Zuercher, R. J. (2017). A current review of doctor-patient computer-mediated communication. Journal of Communication in Healthcare, 10, 22-30.
Liang, Y. (2015). Responses to negative student evaluations on RateMyProfessors.com: The effect of instructor statement of credibility on student lower-level cognitive learning and state motivation to learn. Communication Education, 64, 1-17.
Liang, Y., Bejerano, A., Kearney, P., McPherson, M.B., & Plax, T. G. (2015). The effect of peer and online sources on student course selections and impressions of prospective teachers. Western Journal of Communication, 79, 435-455.
Liang, Y., DeAngelis, B. N., Clare, D. C., Dorros, S. M., & Levine, T. R. (2014). Message characteristics in online product reviews and consumer ratings of helpfulness. Southern Communication Journal, 79, 468-483.
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