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Trash-Talking Robots Fluster Human Opponents

Trash talking has been a tactic long used to fluster game opponents, and now a new study shows that discouraging words can affect game play — even when coming from a robot.

The trash talk in the study was decidedly mild, with utterances such as “I have to say you are a terrible player,” and “Over the course of the game your playing has become confused.” Still, people who played a particular game with the robot — a commercially available humanoid robot known as Pepper — performed worse when the robot discouraged them and better when the robot encouraged them.

Lead author Aaron M. Roth said some of the 40 study participants were technically sophisticated and fully understood that a machine was the source of their discomfort.

“One participant said, ‘I don’t like what the robot is saying, but that’s the way it was programmed so I can’t blame it,'” said Roth, who conducted the study while he was a master’s student in the Carnegie Mellon University (CMU) Robotics Institute.

But the researchers found that, overall, human performance fluctuated regardless of the participants’ technical knowledge.

The study, presented last month at the IEEE International Conference on Robot & Human Interactive Communication (RO-MAN) in New Delhi, India, is a departure from typical human-robot interaction studies, which tend to focus on how humans and robots can best work together.

“This is one of the first studies of human-robot interaction in an environment where they are not cooperating,” said co-author Dr. Fei Fang, an assistant professor in the Institute for Software Research.

The study has significant implications for a world where the number of robots and Internet of things (IoT) devices with artificial intelligence capabilities is expected to grow exponentially.

“We can expect home assistants to be cooperative,” she said, “but in situations such as online shopping, they may not have the same goals as we do.”

The study was an outgrowth of a student project a course that Fang teaches. The students wanted to explore the uses of game theory and bounded rationality in the context of robots, so they designed a study in which humans would compete against a robot in a game called “Guards and Treasures.” A so-called Stackelberg game, researchers use it to study rationality; Fang employs it in her cybersecurity research to study defender-attacker interaction.

For the study, each participant played the game 35 times with the robot, while either enjoying encouraging words from the robot or getting flustered with dismissive remarks. Although the human players’ rationality improved as the number of games played increased, those who were criticized by the robot didn’t score as well as those who were praised.

It’s well-known that a person’s performance is affected by what other people say, but the study shows that humans also respond to what machines say, said Dr. Afsaneh Doryab, a systems scientist at CMU’s Human-Computer Interaction Institute (HCII) during the study and now an assistant professor in Engineering Systems and Environment at the University of Virginia.

This machine’s ability to prompt responses could have implications for automated learning, mental health treatment and even the use of robots as companions, she said.

Future work might focus on nonverbal expression between robots and humans, said Roth, now a Ph.D. student at the University of Maryland. Fang suggests that more needs to be learned about how different types of machines — say, a humanoid robot as compared to a computer box — might evoke different responses in humans.

Source: Carnegie Mellon University

Trash-Talking Robots Fluster Human Opponents

Traci Pedersen

Traci Pedersen is a professional writer with over a decade of experience. Her work consists of writing for both print and online publishers in a variety of genres including science chapter books, college and career articles, and elementary school curriculum.

APA Reference
Pedersen, T. (2019). Trash-Talking Robots Fluster Human Opponents. Psych Central. Retrieved on November 24, 2020, from
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Last updated: 2 Dec 2019 (Originally: 2 Dec 2019)
Last reviewed: By a member of our scientific advisory board on 2 Dec 2019
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