Facilitating Human-Robot Interactions through Humor
Humor is an important feature in human communication that can be leveraged to create more naturalistic and lifelike interactions with robots and humor potentialities can be increased through the delivery of user-personalized humor in naturalistic settings. However, the lack of context, the disregard of user’s preferences, and the over-reliance on certain formats of jokes, such as word puns or one-liners, are still limitations found in a large number of current approaches to humor in human-robot interactions (HRI). The AGENTS - Automatic generation of humor for social robots project created databases of jokes in Portuguese and English in order to investigate the role of humor in HRI taking into account some user characteristics, including their attitudes towards robots and their humor style. The main study involved the creation of an entertainment task and the adaptation of a humor game for the HRI context, during which users' perceptions of the task and robots, as well as physiological measures were assessed, and interaction behavior was analyzed. Preliminary results suggest that a robot that uses humor is perceived as being warmer and more competent than a robot that does not use humor, increasing its emotional value. These results and the developed datasets will be relevant for future research in HRI and are expected to contribute to the development of more socially effective robots, deployed in complex naturalistic interaction settings.
In 1999, Apple introduced a joke generation system that was capable to interact with the user in their OS 9. Although limited to scripted jokes, this was a pioneer system that gave a 'human touch' to the machine and is still used in Apple's operative systems. Nonetheless, humor is a natural emergent feature in everyday conversations and its complexity is hard to capture through scripted, off-context interactions, such as those. Hence, systems that use scripted jokes limit human-robot interaction (HRI) because of their lack of context, the disregard of user’s preferences, and the over-reliance on certain formats of jokes, such as word puns or one-liners.
Humor seems to have positive impacts in people's health. For example, a literature review on the impacts of laughter on blood pressure and heart rate variability found that laughter frequency is associated with improved cardiovascular health, evidence provided by longitudinal studies. However, this review showed that several studies presented sub-optimal levels of quality, so the authors alert for the need of further research to assess the impact of laughter-inducing interventions in cardiovascular health. Either way, humor is a relevant aspect of human communication that may extend to HRI.
In this context, a systematic review of of studies on humor in HRI conducted by Raquel Oliveira, PhD student at CIS-Iscte, and supervisors Patrícia Arriaga, Ana Paiva and Minja Axelsson, found that humor seems to improve the user's perception of the robot, as well as their evaluation of the interaction. However, they point out that few studies have investigated interaction contexts in which humor occurs in a natural way and few have analyzed the effects of HRI on task and robot perception, crossing different types of indicators of emotional, cognitive, and behavioral responses during interaction. Therefore, there is a need to further investigate this emerging theme.
The AGENTS - Automatic generation of humor for social robots project was funded by CMU Portugal program with the following consortium:
Iscte - University Institute of Lisbon, integrating Professor and Researcher Patrícia Arriaga, and researchers Raquel Oliveira and João Barreiros from the Center for Psychological Research and Social Intervention (CIS-Iscte), with the support of the students from the Science on Emotions masters' program, Patrícia Oliveira and Jasmine Sarrouy;
Carnegie Mellon University through the integration of Professor and Researcher Louis-Philippe Morency.
The end-goal of AGENTS was the implementation of humoristic interactions in the context of a group card game involving humans and robots, which was expected to improve interaction outcomes, and increase the positive perception of the robots and the intention to interact with these social agents in the future.
Approach and Results
Implications and Recommendations